CSE 2021 2025 - SyllsbusBook 03sept 2021

School of Engineering and Applied Sciences
B. Tech Computer Science and Engineering
Academic Batch: 2021-2025
Department of Computer Science Engineering

SRM University-AP, Andhra Pradesh
Syllabus B. Tech in Computer Science Engineering
SEMESTER-I
S. No Course Code Course Name L T P C
1 EGL 101/HS E Communicative English /HS Elective 3 0 0 3
2 MAT 112 Single Variable Calculus 3 0 0 3
3 Engineering Physics /Chemistry for
PHY 101/CHE 103 3/2 0 0 3/2
Engineers
4 Engineering Physics Lab /Chemistry for
PHY 101 L/CHE 103 L 0 0 2 1
Engineers Lab
5 BIO 102/ENV 111 Introductory Biology /Environmental Science 3/2 0 0 3/2
6 ***/ENV 111 L ***/Environmental Science Lab 0/0 0/0 0/2 0/1
7 CSE 105 Introduction to Programming Using C 3 0 0 3
8 CSE 105 L Introduction to Programming Using C Lab 0 0 2 1
9 ISES 101 Industry Specific Employability Skills-I 1 1 0 1
** No Lab for Introductory Biology
Total 18/17
SEMESTER-II
1 EGL 101/HS E Communicative English /HS Elective 3 0 0 3
2 MAT 121 Multi variable Calculus 3 0 0 3
3 ENG 111 Basic Electronics 3 0 0 3
4 ENG 111 L Basic Electronics Lab 0 0 2 1
5 CSE 107 Data Structures 3 0 0 3
6 CSE 107 L Data Structures Lab 0 0 2 1
7 Chemistry for Engineers /Engineering
CHE 103/ PHY 101 2/3 0 0 2/3
Physics
8 Chemistry for Engineers Lab /Engineering
CHE 103 L/PHY 101 L 0 0 2 1
Physics Lab
9 ENV 111/BIO 102 Environmental Science/ Introductory Biology 2/3 0 0 2/3
10 ENV 111 L/*** Environmental Science Lab/*** 0/0 0/0 2/0 1/0
11 CSE 130 Industry Standard Coding Practice-I 0 0 4 1
12 ISES 102 Industry Specific Employability Skills-II 1 1 0 1
** No Lab for Introductory Biology
Total 22/23
SEMESTER-III
1 MAT 141 Discrete Mathematics 3 0 0 3
2 CSE 206 Object Oriented Programming with C++ 3 0 0 3
3 CSE 206 L Object Oriented Programming with C++ Lab 0 0 2 1
4 CSE 201 Design and Analysis of Algorithms 3 0 0 3
5 CSE 201 L Design and Analysis of Algorithms Lab 0 0 2 1
6 ECE 211 Digital Electronics 2 1 0 3
7 ECE 211 L Digital Electronics-Lab 0 0 2 1
8 CSE 106 L Hands on Using Python 0 0 4 2
9 CSE 231 Industry Standard Coding Practice-II 0 0 4 1
10 ECO 121 Principles of Economics 3 0 0 3
11 ISES 201 Industry Specific Employability Skills-III 1 1 0 1
Total 22
SEMESTER-IV
1 MAT 221 Probability and Statistics for Engineers 3 0 0 3
2 MAT 131 Differential Equations 3 0 0 3
3 CSE 204 Computer Organization and Architecture 3 0 0 3
4 CSE 204 L Computer Organization and Architecture Lab 0 0 2 1
5 CSE 301 Operating System 3 0 0 3
6 CSEC 301 L Operating System Lab 0 0 2 1
7 CSE 207 Java Programming 3 0 0 3
8 CSE 207 L Java Programming Lab 0 0 2 1
9 CSE 203 Formal Languages and Automata Theory 3 0 0 3
10 ISES 202 Industry Specific Employability Skills-IV 1 1 0 1
11 CSE 233 Industry Standard Coding Practice-III 0 0 4 1
Total 23
SEMESTER-V
1 MAT 211 Linear Algebra 3 0 0 3
2 CSE 303 Computer Networks 3 0 0 3
3 CSE 303 L Computer Networks Lab 0 0 2 1
4 CSE 306 Compiler Design 3 0 0 3
5 CSE 306 L Compiler Design Lab 0 0 2 1
6 CSE 304 Database Management System 3 0 0 3
7 CSE 304 L Database Management System Lab 0 0 2 1
8 CSE SE 1 CS Stream Elective 1 3 0 0 3
9 CSE SE 1 L CS Stream Elective 1 Lab 0 0 2 1
10 OE Open Elective 1 3/4 0 0 3/4
11 CSE 332 Industry Standard Coding Practice-IV 0 0 4 1
12 ISES 301 Industry Specific Employability Skills-V 1 1 0 0
Total 23/24
SEMESTER-VI
1 CSE 305 Software Engineering 3 0 0 3
2 CSE 305 L Software Engineering-Lab 0 0 2 1
5 CSE TE 1 CSE Technical Elective 1 3 0 0 3
8 CSE 340 UROP 0 0 6 3
9 ISES 302 Industry Specific Employability Skills-VI 1 1 0 0
Total 20/22
SEMESTER-VII
5 CSE TE 2 CS Technical Elective 2 3 0 0 3
8 CSE 460 Capstone Project Phase-I 0 0 12 6
Total 23/25
SEMESTER-VIII
2 CSE 461 Capstone Project Phase-II 0 0 12 6
Total 9/10
Total Credits 160/166
Category No of Credits in
Course Category
Code Courses curriculum
Humanities and Social Sciences HS 9 13
Basic Sciences BS 11 25
Engineering Sciences ES 11 19
Professional Core C 23 48
SE 8 16
Professional Elective
TE 2 6
Open Elective OE 6 18/24
Project PR 3 15
Total 73 160/166
List of Stream Specific Electives
Course Code Course Name L T P C
Artificial Intelligence and Machine Learning Stream
CSE 413 Artificial Intelligence 3 0 0 3
CSE 413 L Artificial Intelligence Lab 0 0 2 1
CSE 336 Machine Learning 3 0 0 3
CSE 336 L Machine Learning Lab 0 0 2 1
CSE 314 Digital Image Processing 3 0 0 3
CSE 314 L Digital Image Processing Lab 0 0 2 1
CSE 412 Principles of Soft Computing 3 0 0 3
CSE 412 L Principles of Soft Computing Lab 0 0 2 1
Cyber Security Stream
CSE 337 Cryptography 3 0 0 3
CSE 337 L Cryptography Lab 0 0 2 1
CSE 315 Network Security 3 0 0 3
CSE 315 L Network Security Lab 0 0 2 1
CSE 410 Mobile and Wireless Security 3 0 0 3
CSE 410 L Mobile and Wireless Security Lab 0 0 2 1
CSE 414 Internet Protocols and Networking 3 0 0 3
CSE 414 L Internet Protocols and Networking Lab 0 0 2 1
Big data Analytics Stream
CSE 310 Data warehousing and Mining 3 0 0 3
CSE 310 L Data warehousing and Mining Lab 0 0 2 1
CSE 338 Applied Data Science 3 0 0 3
CSE 338 L Applied Data Science Lab 0 0 2 1
CSE 417 Principles of Big data Management 3 0 0 3
CSE 417 L Principles of Big data Management Lab 0 0 2 1
CSE 419 Information Retrieval 3 0 0 3
CSE 419 L Information Retrieval Lab 0 0 2 1
Distributed and Cloud Computing Stream
CSE 316 Distributed Systems 3 0 0 3
CSE 316 L Distributed Systems Lab 0 0 2 1
CSE 318 Cloud Computing 3 0 0 3
CSE 318 L Cloud Computing Lab 0 0 2 1
CSE 416 Cloud Data Management 3 0 0 3
CSE 416 L Cloud Data Management Lab 0 0 2 1
CSE 418 Service Oriented Computing 3 0 0 3
CSE 418 L Service Oriented Computing Lab 0 0 2 1
Internet of Things Stream
CSE 337 Cryptography 3 0 0 3
CSE 337 L Cryptography Lab 0 0 2 1
CSE 318 Cloud computing 3 0 0 3
CSE 318 L Cloud computing Lab 0 0 2 1
CSE 317 Embedded Systems 3 0 0 3
CSE 317 L Embedded Systems Lab 0 0 2 1
CSE 319 IoT Design Protocols 3 0 0 3
CSE 319 L IoT Design Protocols Lab 0 0 2 1
List of Technical Electives

Course Code Course Name L T P C
CSE 320 Web Programming 3 0 0 3
CSE 321 Human Computer Interaction 3 0 0 3
CSE 322 Advanced Computer Architecture 3 0 0 3
CSE 323 Natural Language Processing 3 0 0 3
CSE 324 Computer Graphics 3 0 0 3
CSE 325 Advanced Data Structures and Algorithms 3 0 0 3
CSE 326 Distributed Operating Systems 3 0 0 3
CSE 420 Data and Web Mining 3 0 0 3
CSE 421 Complexity Theory 3 0 0 3
CSE 422 Software Project Management 3 0 0 3
CSE 423 Multimedia 3 0 0 3
CSE 424 Deep learning 3 0 0 3
CSE 425 Advanced Database Management Systems 3 0 0 3
CSE 426 Fog Computing 3 0 0 3
CSE 427 Parallel Algorithms 3 0 0 3
CSE 428 Web Services 3 0 0 3
CSE 429 Advances in Data Mining 3 0 0 3
SEMESTER - I
SEMESTER-I
Credits
Course Code Course Name Course Category
L T P C
EGL 101 Communicative English HS 3 0 0 3
UNIT I
Course Introduction and Overview. Tenses Principles of Sentence Structure & Paragraph Writing
(S+V+O).
UNIT II
The Fundamentals of Speech (Ethos, Pathos & Logos) Verbal & Nonverbal Communication
Fundamentals of Personal, Informative, and Scientific Speech.
UNIT III
Listening Skills: Definition, Barriers, Steps to Overcome Listening to Influence, Negotiate Note taking
& Making while Listening.
UNIT IV
Read to Skim, and Scan Read to Comprehend (Predict, Answer Questions & Summarize) Read to
Understand.
UNIT V
Write to Inform – I News, Emails, Write to Inform- II Notice, Agenda & Minutes, Write to Define
(Definitions & Essays).
TEXTBOOKS/REFERENCES
1. Shoba, Lourdes. (2017). Communicative English: A Workbook. U.K: Cambridge University
Press.
2. Steven, Susan, Diana. (2015). Communication: Principles for a Life Time. U.S.A: Pearson 6th
Ed.
3. Publication Manual of the American Psychological Association, (2010). 6th Ed.
4. Kosslyn, S.M. "Understanding Charts and Graphs", Applied Cognitive Psychology, vol. 3, pp.
185-226, 1989.
SEMESTER-I
Credits
L T P C
MAT 112 Single Variable Calculus BS 3 0 0 3
UNIT I: DERIVTIVES AND DIFFERENTITATION

Limit, Continuity and limits of quotients, Derivatives and its geometrical Interpretation, Derivative as
a function and calculating derivative, Leibnitz notation and higher derivatives, Trigonometric
functions, Linear Approximations, Product and quotient rules, Chain rule, Implicit differentiation,
Inverse, exponential and logarithm functions.
UNIT II: APPROXIMATIONS AND THEIR APPLICATIONS

Measurement error of linear approximation, Quadratic approximation, Newton’s method, 1 and 2nd
derivative test, Limits and asymptotic, Max min problems, Related application in real-life problems.
UNIT III: THE INTEGRAL AND INTEGRATION THEORY

Mean Value Theorem, Differentials and anti-derivatives, Differential equations, The definite integral,
First and Second Fundamental Theorem of Calculus.
UNIT IV: DIFFERENT INTEGRATION TECHNIQUES AND

APPLICATIONS OF CALCULUS
Areas and Volumes, Average value, Probability, Numerical Integration, Integrals of Trigonometric
Power, Trigonometric substitution, Partial fractions, Integration by Parts, Arc length and Surface area.
UNIT V: POLAR CO-ORDINATE SYSTEMS AND INFINITE SERIES

Parametric curves, Polar co-ordinates, L’Hospital’s rule, Improper Integrals, Infinite Series, Taylor’s
series.
TEXTBOOKS
1. R. G. Bartle and D. R. Sherbert, Introduction to Real Analysis, Third edition, Wiley India,
2005.
2. S. R. Ghorpade and B. V. Limaye, An Introduction to Calculus and Real Analysis.
3. Michael Spivak, Calculus, Third Edition, Cambridge University, 2008.
REFERENCES
1. G. B. Thomas, Jr. and R. L. Finney, Calculus and Analytic Geometry, 3rd Ed.,
Pearson Education India 9th Edition 1999.
2. P.M. Fitzpatrick, Advanced Calculus, 2nd Edition, AMS Indian Edition, 2010.
SEMESTER-I / SEMESTER-II
Credits
L T P C
PHY 101 Engineering Physics BS 3 0 0 3
UNIT I: INTRODUCTION TO VECTOR ALGEBRA

Gradient, Divergence and curl and their physical significances, Gauss and Stokes theorems, Vector
operators in different coordinate (Curvilinear, Cartesian, Cylindrical and spherical) systems.
UNIT II: ELECTROSTATICS

Coulomb’s law, Gauss law, Electric field, Electrostatic Potential, Potential energy of system of charges
Boundary Value problems, capacitance.
UNIT III: DIELECTRICS AND POLARIZATION

Electric dipole and dipole moment, Electric potential due to dipole, Electric field intensity due to
dipole, Polarization P, Electric displacement D, Electric susceptibility and dielectric constant, Bound
volume and surface charge densities, Electric field at an exterior and interior point of dielectric.
UNIT IV: MAGNETOSTATICS

Biot-Savart law, Ampere’s law for force between two current carrying loops, Ampere’s circuital law
Equation of continuity, Energy density in magnetic field, magnetization of matter (B, H, M)
Magnetic susceptibility and permeability, Hysteresis loss, B-H curve, Diamagnetic, paramagnetic and
ferromagnetic substances.
UNIT V: INTRODUCTION TO ELECTRODYNAMICS

Time varying fields: Faradays law of induction, generalization of Amperes’ law, Maxwell’s equation
(Differential and Integral form), Wave equation and plane waves in free space.
TEXTBOOKS
1. MIT-- 8.02X online course material.
2. Introduction to Electrodynamics (4rd Edition) - David J. Griffiths (Publisher - PHI Learning,
Eastern Economy Editions, 2012).
3. Electricity and Magnetism (Reprints 2007, 1st Edition 2001) A. S. Mahajan, A. A. Rangwala,
(Publisher - McGraw-Hill Education).
REFERENCES
1. Electricity and magnetism Edward M Purcell, David J Morin, 3rd edition, Cambridge
University, 2013.
2. Classical Electrodynamics (3rd Edition) - John David Jackson. (Publisher – Wiley).
Credits
L T P C
PHY 101 L Engineering Physics Lab BS 0 0 2 1
LIST OF PRACTICAL EXPERIMENTS

1. Revisions of Vernier caliper and Screw Gauge measurement methods.
2. Plotting experimental data in graphs and error analysis.
3. To determine the moment of inertia of a flywheel.
4. Measurement of time period for a given compound pendulum with different lengths.
5. To determine radius of gyration of a given pendulum.
6. Verification of Stefan`s Law.
7. Measurement of specific heat capacity of any given material.
8. Verify of Hooke’s law and to determine spring contact for given spring combinations.
9. To determine the rigidity modulus of steel wire by torsional oscillations.
10. To calculate Young’s modulus of a given material by deflection method.
11. To measure the capacitance as a function of area and distance between the plates.
12. To determine the dielectric constant of different dielectric materials.
13. Measurement of the induced voltage impulse as a function of the velocity of the magnet.
14. Calculation of the magnetic flux induced by a falling magnet as a function of the velocity of
the magnet.
15. To study the magnetic field along the axis of a current carrying circular loop.
16. To study the dependency of magnetic field on the diameter of coil.
17. To investigate the spatial distribution of magnetic field between coils and determine the
spacing for uniform magnetic field.
18. To demonstrate the superposition of the magnetic fields of the two individual coils.
19. Study of B-H-Curve To study permeability curve of a given material.
Credits
L T P C
BIO 102 Introductory Biology BS 3 0 0 3
UNIT I: BASIS OF LIFE AND DIVERSITY

Molecular evolution, Elements to molecules: water, carbohydrates, lipids, proteins, nucleic acids,
vitamins and minerals. Diversity of life: virus, bacteria, archea and eukarya. Concept of terrestrial,
aquatic and amphibians. Mode of energy & carbon utilization-auto, hetero and lithothrophs.
UNIT II: CELL BIOLOGY

Cell: morphology, cell organelles and functions. Concept of unicellular and multicellular organisms.
Cell cycle and cell division: mitosis and meiosis. Basis of cell-cell communication and signaling.
UNIT III: MOLECULAR BIOLOGY

DNA and Chromosomes: structure and organization, DNA replication, Transcription, Translation.
Introduction to genetic engineering.
UNIT IV: ENZYMES AND APPLICATIONS

Introduction to enzymes; classification, parameters influencing the enzyme activity, mechanism of
enzyme action and enzyme inhibition. Commercial applications of microorganisms and enzymes.
UNIT V: BIOLOGICAL SEQUENCES AND DATABASES

DNA and Protein sequences, Concept of genomics, transcriptomics, proteomics and metabolomics.
File formats of sequence storage: FASTA file, GenBank. Biological databases – NCBI and EMBL
browsers, KEGG and UniProt databases. Usefulness of biological Metadata-Array expression and
1000 genomes. Application of BLAST and Protein/Gene ID conversion.
TEXTBOOKS
1. Thrives in Biochemistry and Molecular Biology, Edition 1, 2014, Cox, Harris, Pears,
Oxford University Press.
2. Exploring Proteins, Ed. 1, 2014, Price and Nairn,Oxford University Press.
3. Thrives in Cell Biology, Ed. 1, 2013, Qiuyu Wang, Cris Smith and Davis, Oxford
University Press.
REFERENCES
1. Cooper, G.M., Housman, R.E. The cell: a molecular approach. (2009).ASM Press,
Washington D. C.
2. Lehninger, A. L., Nelson, D.L., &Cox, M. M. Lehninger principles of biochemistry.
(2000). Worth Publishers, New York.
3. Wilson, K., Walker, Principle and techniques of biochemistry and molecular biology,
(2005). 6thedn. Cambridge University Press, Cambridge.
4. Harvey Lodish, Arnold Berk and Chris A. Kaiser, Molecular Cell Biology, Ed. 8, 2016,
W. H Freeman & Co (Sd).
5. Bruce Alberts, Alexander D. Johnson, Julian Lewis, David Morgan, Martin Raff, Keith
Roberts, and Peter Walter. 2014. Molecular Biology of the Cell. (Sixth Edition). W. W.
Norton & Company.
6. Scott Freeman, Kim Quillin, Lizabeth Allison, Michael Black, Emily Taylor, Greg
Podgorski and Jeff Carmichael. 2016. Biological Science. (6th Edition). Pearson.
7. Bruce Alberts, Dennis Bray, Karen Hopkin, Alexander D. Johnson, Julian Lewis, Martin
Raff, Keith Robert and Peter Walter. 2014. Essential Cell Biology. (4th Edition). W. W.
Norton & Company.
8. Lisa A. Urry, Michael L. Cain, Steven A. Wasserman, Peter V. Minorsky, Jane B. Reece.
2016. Campbell Biology (11th Edition). Pearson.
9. Peter H Raven, George B Johnson, Kenneth A. Mason, Jonathan Losos and Susan Singer.
2016. Biology. (11th Edition). McGraw-Hill Education.
SEMESTER-I
Credits
L T P C
CSE 105 Introduction to Programming Using C ES 3 0 0 3
UNIT I: INTRODUCTION:
Computer systems, hardware, and software. Problem solving: Algorithm / Pseudo code, flowchart,
program development steps Computer languages: Machine, symbolic and high-level languages
Creating and Running Programs: Writing, editing (any editor), compiling (gcc), linking, and executing
in Linux environment Structure of a C program, identifiers Basic data types and sizes. Constants,
Variables Arithmetic, relational and logical operators, increment and decrement operator’s Conditional
operator, assignment operator, expressions Type conversions, Conditional Expressions Precedence
and order of evaluation, Sample Programs.
UNIT II:
SELECTION & DECISION MAKING: if-else, null else, nested if, examples, Multi-way selection:
switch, else-if, examples.
ITERATION: Loops - while, do-while and for, break, continue, initialization and updating, event and
counter controlled loops and examples.
ARRAYS: Concepts, declaration, definition, storing and accessing elements, one dimensional, two
dimensional and multidimensional arrays, array operations and examples. Character arrays and string
manipulations.
UNIT III: MODULAR PROGRAMMING

Functions - Basics, parameter passing, storage classes extern, auto, register, static, scope rules, user
defined functions, standard library functions, Passing 1-D arrays, 2-D arrays to functions. Recursive
functions - Recursive solutions for fibonacci series, towers of hanoi. C Pre-processor and header files.
UNIT IV: POINTERS

Concepts, initialization of pointer variables, pointers as function arguments, passing by address,
dangling memory, address arithmetic, character pointers and functions, pointers to pointers, pointers
and multi-dimensional arrays, dynamic memory management functions, command line arguments.
UNIT V: ENUMERATED, STRUCTURE AND UNION TYPES

Structures - Declaration, definition, and initialization of structures, accessing structures, nested
structures, arrays of structures, structures and functions, pointers to structures, self-referential
structures. Unions, typedef, bit-fields, program applications. Bit-wise operators: logical, shift, rotation,
masks.
FILE HANDLING: Concept of a file, text files and binary files, formatted I/O, file I/O operations
and example programs.
TEXTBOOKS
1. The C programming Language by Brian Kernighan and Dennis Richie.
REFERENCES
1. Problem Solving and Program Design in C, Hanly, Koffman, 7 edition, PEARSON 2013.
th
2. Programming in C, Pradip Dey and Manas Ghosh, Second Edition, OXFORD Higher
Education, 2011.
3. Programming in C, A practical approach Ajay Mittal PEARSON.
4. Programming in C, B. L. Juneja, Anith Seth, First Edition, Cengage Learning.
SEMESTER-I
Credits
L T P C
CSE 105 L Introduction to Programming Using C Lab ES 0 0 2 1
LIST OR PRACTICAL EXPERIMENTS

Week-1: Basic C programs
a. Calculation of the area of triangle.
b. Swap two numbers without using a temporary variable.
c. Find the roots of a quadratic equation.
d. Takes two integer operands and one operator form the user, performs the operation and
then prints the result.
1. Week-2: Loops
a. Find the sum of individual digits of a positive integer and find the reverse of the given
number.
b. Generate the first n terms of Fibonacci sequence.
c. Generate all the prime numbers between 1 and n, where n is a value supplied by the
user.
d. Print the multiplication table of a given number n up to a given value, where n is entered
by the user.
2. Week-3: Loops
a. Decimal number to binary conversion.
b. Check whether the given number is Armstrong number or not.
c. Triangle star patterns
I II III
3. Week-4: Arrays
a. Interchange the largest and smallest numbers in the array.
b. Searching an element in an array
c. Sorting array elements.
4. Week-5: Matrix
a. Transpose of a matrix.
b. Addition and multiplication of 2 matrices.
5. Week-6: Functions
a. (nCr) and (nPr) of the given numbers
b. 1+x+x \2+x \3!+x \4!+………..X \n!
2 3 4 n
6. Week-7: Functions and array

a. Function to find both the largest and smallest number of an array of integers.
b. Liner search.
c. Replace a character of string either from beginning or ending or at a specified location.
7. Weak-8: Pre-processor directives

a. If Def
b. Undef
c. Pragma
8. Weak-9: Structures
a. Reading a complex number
b. Writing a complex number.
c. Addition of two complex numbers
d. Multiplication of two complex numbers
9. Weak-10: String operations without using the built-in functions

a. Concatenate two strings
b. Append a string to another string.
c. Compare two strings
d. Length of a string
e. Find whether a given string is palindrome or not
10. Weak-11: Pointers

a. Illustrate call by value and call by reference.
b. Reverse a string using pointers
c. Compare two arrays using pointers
11. Weak-12: Pointers and array

a. Array of Int and Char Pointers.
b. Array with Malloc(), calloc() and realloc().
12. Weak-13: Recursion

a. To find the factorial of a given integer.
b. To find the GCD (greatest common divisor) of two given integers.
c. Towers of Hanoi
13. Weak-14: File Operations

a. File copy
b. Word, line and character count in a file.
14. Weak-15: Command line arguments

a. Merge two files using command line arguments.
SEMESTER-I
Credits
L T P C
ISES 101 Industry Specific Employability Skills-I HS 1 1 0 1
UNIT I: QUANTS
Speed calculations, Time and Distance, Problems on Trains, Boats and Streams, Races And Games,
Escalator Problems, Time and Work , Chain Rule, Pipes and cistern, Simplification , surds and indices,
Square roots and cube roots, Functions.
UNIT II: REASONING

Number Series, Alphabet series, Odd Man Out, Missing number, Wrong number, Analogies,
Mathematical Operations, Calendars, Clocks, Cryptarithmetic, Identification of Cross-Variable
Relation, Sudoku.
UNIT III: VERBAL

Basic sentence structure: Nouns, Pronouns, Adjectives. Parts of speech. Degree of comparison.
Articles, conditionals, and sentences (kinds). Verb tense. Sentence formation. Paragraph formation,
change of voice, Change of speech, Synonyms, Antonyms.
UNIT IV: COMMUNICATION SKILLS

Self-Introduction, Presentations, Email Etiquette
TEXTBOOKS/REFERENCE BOOKS/OTHER READING MATERIAL

1. Mitchell S. Green – 2017, Know Thyself: The Value and Limits of Self-Knowledge.
2. Debbie Hindle, Marta Vaciago Smith - 2013 , Personality Development: A Psychoanalytic
Perspective.
3. Lani Arredondo - 2000, Communicating Effectively.
4. Patsy McCarthy, Caroline Hatcher - 2002, Presentation Skills: The Essential Guide for
Students.
5. Martha Davis, Elizabeth Robbins Eshelman, Matthew McKay - 2008, Time Management and
Goal Setting: The Relaxation and Stress.
6. Arun Sharma – How to prepare for Quantitative Aptitude, Tata Mcgraw Hill.
7. RsAgarwal,A Modern Approach to Verbal and Non Verbal Reasoning,S.Chand Publications.
8. Verbal Ability and Reading comprehension-Sharma and Upadhyay.
9. Charles Harrington Elstor, Verbal Advantage: Ten Easy Steps to a Powerful Vocabulary, Large
Print, September 2000.
10. GRE Word List 3861 – GRE Words for High Verbal Score, 2016 Edition.
11. The Official Guide to the GRE-General Revised Test, 2nd Edition, Mc Graw Hill Publication.
12. English grammar and composition – S.C. Gupta.
13. R.S. Agarwal – Reasoning.
14. Reasoning for competitive exams – Agarwal.
SEMESTER - II
SEMESTER-II
Credits
L T P C
MAT 121 Multi-Variable Calculus BS 3 0 0 3
UNIT I: VECTOR AND MATRICES

Vectors, Dot product, Determinants; cross product, Matrices; inverse matrices, Square systems;
equations of planes, Parametric equations for lines and curves, Velocity, acceleration, Kepler's second
law.
UNIT II: PARTIAL DERIVATIVES

Level curves; partial derivatives; tangent plane approximation, Max-min problems; least squares,
Second derivative test; boundaries and infinity, Differentials; chain rule, Gradient; directional
derivative; tangent plane, Lagrange multipliers, Non-independent variables, Partial differential
equations.
UNIT III: DOUBLE INTEGRAL AND LINE INTEGRALS IN THE PLANE

Double integrals, Double integrals in polar coordinates; applications, change of variables, Vector fields
and line integrals in the plane, Path independence and conservative fields, Gradient fields and potential
functions, Green's theorem, Flux; normal form of Green's theorem, simply connected regions.
UNIT IV: TRIPLE INTEGRALS IN 3D

Triple integrals in rectangular and cylindrical coordinates, Spherical coordinates; surface area, Vector
fields in 3D; surface integrals and flux, Divergence theorem: applications and proof.
UNIT V: SURFACE INTEGRAL IN 3D

Line integrals in space, curl, exactness, and potentials, Stokes' theorem, Topological considerations,
Maxwell's equations.
TEXTBOOKS
1. Edwards, Henry C., and David E. Penney. Multivariable Calculus. 6th ed. Lebanon, IN:
Prentice Hall, 2002.
2. G. B. Thomas, Jr. and R. L. Finney, Calculus and Analytic Geometry, 9th Edn., Pearson
Education India, 1996.
REFERNCES
1. T. M. Apostol, Calculus - Vol.2, 2nd Edn., Wiley India, 2003.
SEMESTER-II
Credits
L T P C
ENG 111 Basic Electronics ES 3 0 0 3
UNIT I: ELECTRICAL QUANTITIES AND THEIR MEASUREMENT

Ohm’s law, permanent magnet moving coil (PMMC) instrument, Ammeter and Voltmeter using
PMMC, Measurement of resistance using Wheat Stone’s Bridge and Kelvin’s double bridge,
measurement of capacitance using Schering’s bridge and De Sautee’s bridge, and measurement of
inductance using Maxwell’s bridge and Hay’s bridge. Operation of the oscilloscope.
UNIT II: SEMICONDUCTOR DEVICES

Forward and reverse bias characteristics of PN junction diode. Design of half-wave, full wave, bridge
rectifiers, clipping and clamping using PN junction diode. Bipolar junction transistors (BJTs),
common-base, common-collector and common-emitter configurations using BJTs. Voltage and
current gain, transistor as amplifier and buffer. Photodiode and phototransistor.
UNIT III: A.C. CIRCUITS AND OPERATIONAL AMPLIFIER

Phasor analysis, impedance and reactance, resonance, tuned circuits using R-L-C components, series
reactance and resistance, parallel reactance and resistance. Characteristics of an operational amplifier,
inverting and non-inverting op-amps, integrator and differentiator design using op-amp. Differential
operational amplifier and common mode rejection ratio.
UNIT IV: ELECTRONIC FILTERS

Low and high frequency noise in electronic circuits, basic low-pass, high-pass, band-pass and band-
reject passive filters design using resistor, capacitor and inductor. Fourier transform, magnitude and
phase response, bandwidth, bode plots. Design and analysis of higher order filters. Active filter design
using operational amplifier, applications of electronic filters.
UNIT V: DIGITAL LOGIC FUNDAMENTALS

Number systems: binary, decimal, octal and hexadecimal number systems, number system
conversions. Logic gates: AND, OR, NOT, NAND, NOR, X-OR, X-NOR. Logic gates design using
PN diodes. De Morgan’s laws, Karnaugh maps. Basic combinational logic blocks: half adder, half
subtractor, full adder, full subtractor, multiplexer and de multiplexer.
TEXTBOOKS
1. Principles of electronics by V K Mehta & Rohit Mehta, 2010 edition, S Chand and
Co. Publisher, ISBN: 9788121924504.
2. Electronic devices and circuits by David A. Bell, 2008 edition, Oxford University Press,
ISBN: 9780195693409.
3. Introduction to digital logic design by John P. Hayes, 1993 edition, Pearson Edition,
ISBN: 9780201154610.
REFERENCES
1. Electronic measurements and Instrumentation by A K Sawhney, 2015 edition, Dhanpat Rai
and Co., ISBN: 9788177001006.
2. Pulse, Digital and Switching waveforms by Mill man and Taube, 2011 edition, Tata McGraw
Hill, ISBN: 9780071072724.
SEMESTER-II
Credits
L T P C
ENG 111 L Basic Electronics Lab ES 0 0 2 1

1. Verification of Kirchhoff’s laws (KCL, KVL).
2. Study of I-V characteristics of PN junction diode.
3. Design of half-wave rectifier using PN junction diode with and without capacitor filter.
4. Design of positive and negative clipping circuits using PN junction diodes.
5. Study of current and voltage gain characteristics of a NPN transistor in common-emitter
configuration.
6. Drain characteristics of common source JFET.
7. Design of inverting and non-inverting amplifier circuits using op-amp IC 741.
8. Study of integrator and differentiator circuits using op-amp IC 741.
9. Design of Schmitt Trigger Using IC 741.
10. Study of function of digital logic gates (AND, NOT, OR, NAND, NOR).
SEMESTER-II
Credits
L T P C
CSE 107 Data Structures ES 3 0 0 3
UNIT I
Introduction to data structures, Abstract Data Type (ADT), representation and implementation, time
and space requirements of algorithms. Array ADT, representing polynomials, sparse matrices using
arrays and their operations Stacks and Queues: Representation and application, implementation of
stack and queue operations using C.
UNIT II
Linked lists: Single linked lists, implementation of link list and various operation using C, double
linked list, circular list and applications.
UNIT III: TREES

Tree terminology, binary tree, binary search tree, infix to postfix conversion, postfix expression
evaluation. AVL Tree, complete binary tree representation.
UNIT IV: GRAPHS

Graph terminology, representation of graphs, path matrix, BFS (breadth first search), DFS (depth
first search), topological sorting, shortest path algorithms. Priority Queues: Heap structures,
binomial heaps, leftist heaps.
UNIT V: SORTING AND SEARCHING TECHNIQUES

Bubble sort, selection sort, insertion sort, quick sort, merge sort, heap sort, radix sort and
implementation. Linear and binary search methods, implementation; Hashing techniques and
hash functions.
TEXTBOOKS
1. “Data Structure -- A Pseudo code approach with C” by Richard R. Gilberg & Behrouz A.
Forouzan, 2 edition, 2011. Cengage Learning. Imprint: Thomson Press (India) Ltd.
nd
2. “Data Structures Using C” by Aaron M. Tanenbaum, Yedidvah Langsam, and Moshe J.

Augenstein. Pearson Publishers, 2019.
REFERENCES
1. Programming with C, Byron Gottfried, McGraw hill Education, Fourteenth reprint, 2016.
2. “Fundamental of Data Structures”, (Schaums Series) Tata-McGraw-Hill.
3. Data structures and Algorithm Analysis in C, Mark Allen Weiss, Pearson publications,
Second Edition Programming in C. P. Dey and M Ghosh, Second Edition, Oxford
University Press.
4. “Fundamentals of data structure in C” by Horowitz, Sahani & Anderson Freed, Computer
Science Press.
5. G. A. V. Pai: “Data Structures & Algorithms; Concepts, Techniques &
Algorithms” Tata McGraw Hill.
SEMESTER-II
Credits
L T P C
CSE 107 L Data Structures ES 0 0 2 1

1. Week 1 & 2: Simulate the following operations:
a. Conversion of infix expression to postfix expression
b. Evaluation of expressions
c. Assignment-1: Tower of Hanoi is a mathematical puzzle where we have three rods and n disks.
The objective of the puzzle is to move the entire stack to another rod, obeying the following
simple rules:
i. Only one disk can be moved at a time.
ii. Each move consists of taking the upper disk from one of the stacks and placing it on
top of another stack i.e. a disk can only be moved if it is the uppermost disk on a stack.
iii. No disk may be placed on top of a smaller disk
iv. You can choose to use the function move (4, 1, 3, 2), where 4 represents the number of
disks. 1 represents disks on source shaft, 3 represents the destination shaft which holds
the disks after the move and finally 2 represents the intermediate support shaft –
temporary storage. Write a C program to simulate the given problem and: Perform the
algorithmic complexity analysis for the solution you propose.
Resources: https://www.youtube.com/watch?v=YstLjLCGmgg
1. Week 3 & 4: Simulate the following tasks:
a. Implementation the following operations: enqueue, dequeue and finding an element:
i. Linear Queue using arrays
ii. Circular queue arrays
iii. Priority queue singly linked list.
b. Assignment-2: The “4-Queens Problem” consists of placing four queens on a 4 x 4 chessboard
so that no two queens can capture each other. That is, no two queens are allowed to be placed
on the same row, the same column or the same diagonal (both primary and secondary
diagonals). Write a C program to simulate the given problem and perform the algorithmic
complexity analysis for the solution you propose.
Reference(s): Data Structures and Program Design in C by Robert Kruse, C L Tondo, Bruce
Leung and Shashi Mogalla. For pseudocode, refer the following pages 98 to 105.
Online Reference: https://www.youtube.com/watch?v=xFv_Hl4B83A
1. Week 5 &6: Demonstrate the following though simulation:

a. Create a singly linked list and perform the following operations:
i. Add an element at the end of the list
ii. Delete an element from the beginning of the list
iii. Find the middle element of the list
iv. Search the given key form the list
v. Polynomial addition using linked list
vi. Sparse matrix operations using linked list
b. Assignment-3: Let us consider a small but busy airport with only one run-way (shown in
figure). In each time unit, one plane can land or one plane can take off, but not both. Planes
arrive ready to land or to take off at random times, so at any given unit of time, the runway
may be idle or a plan may be landing or taking off, and there may be several planes waiting
either to land or take off. We therefore need two queues, called landing and takeoff, to hold
these planes. It is better to keep a plane waiting on the ground than in the air, so a small
airport allows a plane to take off only if there are no planes waiting to land. Hence, after
receiving requests from new planes to land or take off, our simulation will first service the
head of the queue of planes waiting to land, and only if the landing queue is empty will it
allow a plane to take off. We shall wish to run the simulation through many units of time,
and therefore, we embed the main action of the program in a loop that runs for cur-time
(denoting current time) from 1 to a variable end-time.
Simulate the given scenario using and write the output for different inputs.
Reference(s): Data Structures and Program Design in C by Robert Kruse, C L Tondo,

Bruce Leung and Shashi Mogalla. For pseudocode, refer the following pages 139 to 150.
1. Week 7 & 8: Write code to perform the following operations:
a. Develop a code to test whether the given tree is binary tree or not.
b. Implementation of Binary tree traversals techniques – pre-order, in-order, and post-order.
c. Implementation of AVL tree and its operations
d. Assignment-4: Given a mathematical expression, evaluate it using appropriate tree structure.
1. Week 9 & 10: Write the codes to perform the following tasks:
a. Implementation of Graph traversals techniques: i) BFS and ii) DFS.
b. Assignment-5: The Dijkstra’s algorithm is an algorithm that gives the shortest path between
two given vertices of a graph. In this problem we are given a directed graph with each edge having
a non-negative weight. Thus, a solution requires a path of many other that costs least. We can
think of the problem as like this: think graph G as a map of the airline routes, each node of the
graph as the cities and the weights on each edge as the cost of flying from one city to another city.
The solution we have to find a routing from a city v to city w such that the total cost is minimum.
Write a C program to simulate the given problem. That is find the shortest path between node A
and node F in the given graph. Resource: Data Structures and Program Design in C by Robert
Kruse, C L Tondo, Bruce Leung and Shashi Mogalla. For pseudocode, refer the following pages
510 to 514.
1. Week 11 & 12: Implementation of the following algorithms:
a. Linear search
b. Binary search
c. Implementation of Bubble sort algorithm
d. Implementation of Selection sort algorithm
e. Implementations of Merge sort algorithm
1. Week 13 & 14:
a. Implementation of Insertion sort algorithm
b. Implementation of quick sort algorithm
c. Assignment-6: Suppose you work at college library. You are in the middle of a quiet
afternoon when suddenly a shipment of 3928 different books arrives. The books have been
dropped of in one long straight line, but they are all out of order, and the automatic sorting
system is broken. To make matter worse, classes will start tomorrow, which means that first
thing in the morning, students will show up in droves looking for these books. How can you
get them all sorted in time?
Simulate the given scenario using C code. Perform the algorithmic time complexity analysis
for the solution you propose. Also give the space complexity.
Reference(s): Data Structures and Program Design in C by Robert Kruse, C. L. Tondo ,

Bruce Leung and Shashi Mogalla. For pseudocode, refer the following pages 302 to 312.
Online resources: Use the following link to get a better understanding on the problem.
https://www.youtube.com/watch?v=PgBzjlCcFvc
https://www.programiz.com/dsa/quick-sort
1. Week 15: Our Text editor will allow us to read a file into memory i.e., it is stored in the buffer. We
consider each line of text to be a string and buffer will be a list of these lines. we shall then devise
editing commands that will do list operations on lines in buffer and will do string operations on
characters in a single line. Here are few commands;
a. R – Read the text file
b. W – Write to text file
c. I – Insert a new line
d. D – Delete the current line
e. P – Previous line (back up one line in buffer)
f. B – Go to first line of buffer
g. E – Go to last line of buffer
h. Q – Quit the editor
Tasks we do are :
a. Receiving a command from user
b. GetCommand() – this function gets the command from user
c. DoCommand() – this function performs the command
Now we have to perform the command for example if the command is ‘b’ we have to go beginning
of buffer; if it is ‘n’ we must move to next line. All these commands can be performed using switch
case statement. Using the switch case statements we check for the command and specify the
functions to perform the appropriate task.
SEMESTER-II / SEMESTER-I
Credits
L T P C
CHE 103 Chemistry for Engineers BS 2 0 0 2
UNIT I: CHEMICAL BONDING

Ionic, covalent, metallic bonds and hydrogen bonding. Theories of bonding: Hybridization:
Types of hybridization, sp, sp2, sp3, sp3d, d2sp3. Shapes of molecules (VSEPR Theory): BeCl2,
CO2, BF3, H2O, NH3, CH4, PCl5, XeF2, SF6, XeF4. Molecular orbital theory: Linear
combination of atomic orbitals (LCAO Method), bond order, homo-nuclear diatomic molecules
such as H2, O2, N2
UNIT II: PHASE RULE, THERMOCHEMISTRY, AND KINETICS

Definition of the terms used in phase rule with examples. Application of phase rule to one
component system (eg Water). Application of phase rule to two component system (eg Pb-Sn).
Standard terms in thermochemistry and their significance. Heat of combustion, formation and
sublimation (with examples in fuels and propellants). Order and molecularity of reactions, zero
order, first order rate equations, Problems associated with Zero & First order reactions.
UNIT III: CRYSTALLINE MATERIALS

Introduction to solid state materials, difference between crystalline and amorphous systems,
Properties of crystalline materials. Crystal lattice, unit cells, types of crystal systems, types of
unit cells (Bravais lattices) Miller indices, Bragg’s law Problems associated theoretical density
of crystals and Bragg’s equation Introduction to Band theory, metals, insulators, and
semiconductors with examples. Classification of semiconductors, imperfections in crystals,
Frenkel and Schottky defects, doping and devices.
UNIT IV: MATERIALS CHEMISTRY

Introduction to Polymers. Classification of polymers, Thermoplastic and Thermosetting
polymers with examples, Tacticity of polymers, Properties of polymers: Glass transition
temperature (Tg) Properties of polymers: Molecular weight, weight average, Problems
associated with Molecular weight, weight average. Degradation of polymers and biodegradable
polymers, Common Polymers: Elastomer, Conducting polymer, Hardness in water,
demineralization of water. Water treatment: Zeolite process.
UNIT V: ELECTROCHEMICAL DEVICES

Introduction to Electrochemical cells and classification of Electrochemical cells, Primary and
secondary cells with examples. Lead-acid battery and Li+ batteries Li+ batteries and Fuel cells.
TEXTBOOKS
1. A. Bahl, B.S. Bahl, G.D. Tuli, Essentials of Physical Chemistry, (2016), S Chand Publishing
Company
2. B. R. Puri, L. R. Sharma & M. S. Pathania, Principles of Physical Chemistry, 46 th Edition
(2013), Vishal Publication Company
3. D. F. Shriver, P. W. Atkins and C. H. Langford, Inorganic Chemistry, 3rd Ed., Oxford
University Press, London, 2001.
4. V. R. Gowariker, N. V. Viswanathan, J. Sreedhar, Polymer Science, New Age International,
1986. ISBN: 0-85226-307-4.
5. Atkins, P.W.; de Paula, J. (2006). Physical chemistry (8th ed.). Oxford University Press.
ISBN 0-19-870072-5.
Credits
L T P C
CHE 103 L Chemistry for Engineers Lab BS 0 0 2 1

1. Volumetric titration of HCl vs NaOH.
2. Conductometric titration of HCl vs NaOH.
3. Standardization of potassium permanganate by Oxalic acid.
4. Iodometric Determination of Ascorbic Acid (Vitamin C).
5. Determination of hardness of water by EDTA method.
6. Determination of strength of given hydrochloric acid using pH meter.
7. Estimation of iron content of the given solution using potentiometer.
8. Determination of sodium and potassium by flame photometry.
REFERENCES
1. G.H Jeffery, J Bassett, J Mendham, R.C Denny, Vogel’s Text Book of Quantitative
Chemical Analysis, Longmann Scientific and Technical, John Wiley, New York.
2. J.B Yadav, Advanced Practical Physical Chemistry, Goel Publishing House, 2001.
3. A.I Vogel, A.R Tatchell, B.S Furnis, A.J Hannaford, P.W.G Smith, Vogel’s Text Book of
Practical Organic Chemistry, Longman and Scientific Technical, New York, 1989.
4. J.V. McCullagh, K.A. Daggett, J. Chem. Ed. 2007, 84, 1799.
Credits
L T P C
ENV 111 Environmental Science BS 2 0 0 2
UNIT I: ENVIRONMENTAL CRISIS AND SUSTAINABLE DEVELOPMENT

Environment: Structure and functions in an ecosystem; Ecological succession; Ecological pyramids;
Biosphere; Ecological systems and cycles – carbon cycle, water cycle, phosphorous cycle, nitrogen
cycle, oxygen cycle; Broad nature of chemical composition of plants and animals; Natural resources
covering renewable and non-renewable resources, forests, water, minerals, food and land; Energy
sources, growing energy demands.
UNIT II: ECOSYSTEMS

Environmental Pollution: Structure and composition of atmosphere. Pollution – air, water, soil, thermal
and radiation. Effects – acid rain, ozone layer depletion and greenhouse gas emission. Control
measures. Determination of water and air quality – BOD, COD, TDS, AQI.
UNIT III: RENEWABLE AND NON-RENEWABLE RESOURCES

Environmental Biotechnology: Environmental microbiology; Biomarkers; Biosensors; Biofuels;
Biotransformation; Bioremediation, factors affecting bioremediation; Molecular Ecology.
UNIT IV: BIODIVERSITY

Biodiversity and its conservation: Biodiversity hotspots; Values of biodiversity: consumptive use,
productive use, social, ethical, aesthetic and option values; threats to biodiversity – habitat loss,
poaching of wildlife; in-situ and ex-situ conservation.
UNIT V: POLLUTION AND POLICIES

Environmental protection and sustainability: Problems related to urban living, waste management,
climate change, sustainable solutions, environmental regulation, and environmental protection acts in
India and environmental ethics
TEXTBOOKS
1. Basu. M, Xavier. S. “Fundamentals of Environmental Studies”, 1st edition, Cambridge
University Press, 2016.
2. Raina. M. Maier, Ian L. Pepper, Charles. P. “Environmental Microbiology” 2nd edition,
Academic Press, 2004.
REFERENCES
1. Danial. D. C. “Environmental Science”, 8th edition, Jones and Barlett Publishers, MA, 2010.
Credits
L T P C
ENV 111 L Environmental Science Lab BS 0 0 2 1

1. Water parameters- Test for alkalinity and turbidity of water.
2. Determination of dissolved oxygen in water.
3. Test for total suspended solids and total dissolved solids.
4. Determination of total hardness of water by EDTA titration.
5. Determination of biological oxygen demand of wastewater.
6. Determination of chemical oxygen demand of wastewater.
7. Test for iron content in river water.
SEMESTER-II
Credits
L T P C
CSE 130 Industry Standard Coding Practice - I ES 0 0 4 1
UNIT I
Problem solving through Competitive Coding, Problem solving using control structures, Numeric
series and patterns, Code Complexity analysis, Linear/ Logarithmic/ Super linear/ Polynomial/
Exponential/ Factorial Algorithms, Problem solving on rotations of data, Problem solving on Order
statistic problems, Problem Solving Examples Problem solving on matrix data, Memory manipulation
techniques using pointers.
Memory Arithmetic, Problem solving implementing pointer to an array, Memory Layout, overcoming
the segmentation faults, Runtime memory allocation, Coding comparisons of Linear list data structure
and Pointers, examples and Practice problems.
UNIT II
Problem solving on string data, Problem solving on String manipulations, coding problems using string
handling functions, Problem solving on Multi-String Problems, Problem Solving for long strings,
Examples, Practice problems. Problem solving using modular programming, Inter module
communications, scopes of data in the code, Problem solving approaches using recursions, Evaluation
of Recursive algorithms, Significance of mathematical Recurrence Relations, Evaluation of recurrence
relations, Time Analysis, Examples, Practice problems.
UNIT III
Requirement of User-Defined data, Problem solving implementing structures, Nested Structures,
Unions, Enumeration, Usage of Preprocess statements in coding problems, Examples, Practice
Problems Structure member reference, member pointer reference, Coding to form links, Example
codes, Problem solving on operational and traversal logics on linked lists, Problem solving to compare
linked lists, detection of a cycle/merge point, Merging sorted linked lists, coding problems on circular
linked lists/Double linked lists, Examples, Practice problems.
UNIT IV
Problem Solving Problem solving through Linked list coding, traversals, Problem solving to compare
linked lists, detection of a cycle/merge point, Merging sorted linked lists, Circular linked list formation,
Double linked list formation, Examples, Practice problems.
UNIT V
Problem solving through testing, implementing various testing approaches: Test strategy,
Test development, Test execution, Bug fixing, Examples, Practice problems, Problem solving Methods
and techniques. Understanding the problem as math abstract, formation of the logic, Identifying the
corner cases, Examples, Practice problems, Version control systems, Git repositories and working
trees, adding new version of the files to a Git repository, Examples, practice problems.
SEMESTER-II
Credits
L T P C
ISES 102 Industry Specific Employability Skills-II HS 1 1 0 1
UNIT I: QUANTS
Average, Alligation or Mixture, Alligation or Mixture, Percentage, Profit and Loss, True discount,
Partnership, Height and distance.
UNIT II: REASONING

Logical deductions, Syllogism, Image based problems, Coding and Decoding, Cubes and Cuboids,
Inequalities, Input output tracing.
UNIT III: VERBAL

Ordering of sentences, Comprehension, Verbal Analogies, Essential parts of a sentence, One-word
substitutes, Cause and effect, Syllogism.

Sentence formation (Practical), Word group categorization, Casual conversation (Practical), Formal
conversation (interpersonal)
Perspective.
Students.
9. Charles Harrington Elstor, Verbal Advantage: Ten Easy Steps to a Powerful Vocabulary,
Large Print, September 2000.
11. The Official Guide to the GRE-General Revised Test, 2nd Edition, Mc Graw Hill Publication
12. English grammer and composition – S.C. Gupta.
SEMESTER - III
SEMESTER-III
Credits
L T P C
MAT 141 Discrete Mathematics C 3 0 0 3
UNIT I: THE FOUNDATIONS LOGIC AND PROOFS

Propositional Logic, Applications of Propositional Logic, Propositional Equivalences, Predicates and
Quantifiers, Nested Quantifiers, Rules of Inference, Introduction to Proofs, Proof Methods and
Strategy.
UNIT II: SET THEORY

Laws of set theory, Set Operations, Functions, Sequences and Summations, Matrices.
UNIT III: ELEMENTARY NUMBER THEORY, INDUCTION AND RECURSION

Divisibility and Modular Arithmetic, Integer Representations and Algorithms, Primes and
Greatest Common Divisors, Solving Congruence’s; Mathematical Induction, Strong Induction
and Well- Ordering, Recursive Definitions and Structural Induction.
UNIT IV: COUNTING PRINCIPILES

The Basics of Counting, the Pige on hole Principle, Permutations and Combinations, Binomial
Coefficients and Identities, Applications of Recurrence Relations, Solving Linear Recurrence
Relations, Divide-and-Conquer Algorithms and Recurrence Relations.
UNIT V: INTRODCUTION TO GRAPH THEORY

Graphs and Graph Models, Graph Terminology and Special Types of Graphs, Representing
Graphs and Graph Isomorphism, Connectivity, Eulerand Hamilton Paths, Shortest-Path Problems.
TEXTBOOKS
1. Kenneth H. Rosen, Discrete Mathematics and Applications, Seventh edition, Tata
McGraw-Hill,2012.
2. J. P. Tremblay and R. P. Manohar, Discrete Mathematics with Applications to
Computer Science, Tata McGraw-Hill, 1997.
REFERENCES
1. S. Lipschutz and M.L. Lipson, Schaum's Outline of Theory and Problems of Discrete
Mathematics,3rd Ed., Tata McGraw-Hill, 1999.
2. M. K. Venkataraman, N. Sridharan, and N. Chandrasekaran, Discrete Mathematics,
National Publishing Company, 2003.
SEMESTER-III
Credits
L T P C
CSE 206 Object Oriented Programming using C++ C 3 0 0 3
UNIT I: INTRODUCTION
What is object-oriented programming? Comparison of procedural programming and Object-Oriented
Programming - Characteristics of Object-Oriented Languages - C++ Programming Basics: Basic
Program Construction - Data Types, Variables, Constants - Type Conversion, Operators, Library
Functions - Loops and Decisions, Structures - Functions: Simple Functions, passing arguments,
Returning values, Reference Arguments. - Recursion, Inline Functions, Default Arguments - Storage
Classes - Arrays, Strings, Addresses, and pointers. Dynamic Memory management. Linked lists in
C++.
UNIT II: FEATURES OF OBJECT-ORIENTED PROGRAMMING

Introduction to Classes and Objects, Making sense of core object concepts (Encapsulation,
Abstraction, Polymorphism, Classes, Messages Association, Interfaces). Constructors and its types,
Destructors - Passing Objects as Function arguments and Returning Objects from Functions.
UNIT III: POLYMORPHISM

Concept of Polymorphism, Function overloading, examples and advantages of function overloading,
pitfalls of function overloading, Operator overloading, Overloading unary operations. Overloading
binary operators, pitfalls of operators overloading.
UNIT IV: INHERITANCE

Concept of inheritance. Derived class and based class. Derived class constructors, member function,
inheritance in the English distance class, class hierarchies, inheritance and graphics shapes, public and
private inheritance, aggregation: Classes within classes, inheritance, and program.
UNIT V: TEMPLATES AND EXCEPTIONS

Templates: Function templates, Class templates - Exceptions: Need of Exceptions, keywords, Simple
and Multiple Exceptions - Re-throwing Exception and Exception Specifications, Custom Exception.
Standard Template Library: Containers, Algorithms, iterators - potential problems with STL -
Algorithms: find (), count (), sort (), search (), merge () - Function Objects: for each (), transform () -
Sequence Containers: vectors, Lists, Dequeues - Iterators and specialized.
TEXTBOOKS
1. C++ Primer, Stanley B. Lippman, Stanley Lippman and Barbara Moo, Addison-Wesley
Professional, Fifth edition, 2012.
2. C++: The complete reference, Schildt, Herbert. McGraw-Hill/Osborne, Fourth edition, 2017.
REFERENCES
1. Thinking in C++, Bruce, Eckel, Pearson, Second edition, Volume 1, 2002.
2. Object-oriented programming in C++, Robert Lafore, Course Sams Publishing, Fourth edition,
2001.
3. Lischner, Ray. STL Pocket Reference: Containers, Iterators, and Algorithms. " O'Reilly Media,
Inc.", 2003.
SEMESTER-III
Credits
L T P C
CSE 206 L Object Oriented Programming using C++ Lab C 0 0 2 1

Week-1:
1. Takes two integer operands and one operator form the user, performs the operation and then
prints the result.
2. Generate all the prime numbers between 1 and n, where n is a value supplied by the user.
3. Searching an element in an array.
4. To find the factorial of a given integer.
Week-2:
1. Write a program to demonstrate the Inline functions.
1. Programs to understand different function call mechanism.
a. call by reference b. call by value
1. Programs to understand storage specifiers
Week-3:
1. Write a Program to design a class having static member function Named showcount() which
has the property of displaying the number of objects created of the class.
1. Write a Program using class to process Shopping List for a Departmental Store. The list
include details such as the Code No and Price of each item and perform the operations like
Adding, Deleting Items to the list and Printing the Total value of a Order.
Week-4:
1. Write a Program which creates & uses array of object of a class.( for eg. implementing the
list of Managers of a Company having details such as Name, Age, etc..).
1. Write a Program to find Maximum out of Two Numbers using friend function. Note: Here
one number is a member of one class and the other number is member of some other class.
Week-5:
1. Write a Program to swap private data members of classes Named as class_1, class_2 using
friend function.
1. Write a Program to design a class complex to represent complex numbers. The complex
class should use an external function (use it as a friend function) to add two complex
numbers. The function should return an object of type complex representing the sum of two
complex numbers.
Week-6:
1. Write a Program using copy constructor to copy data of an object to another object.
1. Write a Program to allocate memory dynamically for an object of a given class using class’s
constructor.
Week-7:
1. Write a Program to design a class to represent a matrix. The class should have the
functionality to insert and retrieve the elements of the matrix
1. Write a program to design a class representing complex numbers and having the functionality
of performing addition & multiplication of two complex numbers using operator overloading.
Week-8:
1. Write a Program to overload operators like *, <<, >> using friend function. The following
overloaded operators should work for a class vector.
1. Write a program for developing a matrix class which can handle integer matrices of different
dimensions. Also overload the operator for addition, multiplication & comparison of
matrices.
Week-9:
1. Write a program to overload new/delete operators in a class.
1. Write a program in C++ to highlight the difference between overloaded assignment operator
and copy construct.
Week-10:
1. Write a Program illustrating how the constructors are implemented and the order in which
they are called when the classes are inherited. Use three classes Named alpha, beta, gamma such
that alpha, beta are base class and gamma is derived class inheriting alpha & beta
1. Write a Program to design a student class representing student roll no. and a test class
(derived class of student) representing the scores of the student in various subjects and sports class
representing the score in sports. The sports and test class should be inherited by a result class
having the functionality to add the scores and display the final result for a student.
Week-11:
1. Write a program to maintain the records of person with details (Name and Age) and find the
eldest among them. The program must use this pointer to return the result.
1. Write a Program to illustrate the use of pointers to objects which are related by inheritance.
Week-12:
1. Write a program illustrating the use of virtual functions in class.
1. Write a program to design a class representing the information regarding digital library (books,
tape: book & tape should be separate classes having the base class as media). The class should
have the functionality for adding new item, issuing, deposit etc. the program should use the
runtime polymorphism.
Week-13:
1. Write a program to show conversion from string to int and vice-versa.
1. Write a program showing data conversion between objects of different classes.
Week-14:
1. Write a program showing data conversion between objects of different classes and conversion
routine should reside in destination class.
1. Write a program to copy the contents of one file to another.
Week-15:
1. Write a program to implement the exception handling.
1. Write a program to maintain the elementary database of employee using file concepts.
SEMESTER-III
Credits
L T P C
CSE 201 Design and Analysis of Algorithms C 3 0 0 3
Algorithmic thinking & motivation with examples, Reinforcing the concepts of Data Structures with
examples. Complexity analysis of algorithms: big O, omega, and theta notation, Analysis of Sorting
and Searching, Hash table, Recursive and non-recursive algorithms.
UNIT II: GENERAL PROBLEM SOLVING (GPS) TECHNIQUES

Divide and conquer: Merge sort, Quicksort, BST, Master method for Complexity analysis
Greedy method: Fractional Knapsack, Minimum spanning trees (Prim’s & Kruskal’s), Shortest paths:
Dijkstra’s algorithm, Huffman coding Dynamic Programming: 0/1 Knapsack, All-to-all shortest paths.
UNIT III
BFS & DFS, Backtracking: 8-Queen’s problem, Knight’s tour, Travelling Salesman Problem (TSP),
Branch-and-bound: 16-puzzle problem, TSSP, Randomized algorithms: Playing Cards, Scheduling
algorithms.
UNIT IV
Pattern matching algorithms: Brute-force, Boyer Moore, KMP algorithms. Algorithm analysis:
Probabilistic Analysis, Amortized analysis, Competitive analysis.
UNIT V
Non-polynomial complexity: examples and analysis, Vertex cover, set cover, TSP, 3-SAT
Approximation Algorithms: Vertex cover, TSP, Set cover.
TEXTBOOKS
1. Cormen, Leiserson, Rivest, Stein, "Introduction to Algorithms", 3rd Edition, MIT press, 2009.
2. Parag Dave & Himanshu Dave, "Design and Analysis of Algorithms", Pearson Education,
2008.
REFERENCES
1. Michel Goodrich, Roberto Tamassia, “Algorithm design-foundation, analysis & internet
examples”, Wiley., 2006.
2. A V Aho, J E Hopcroft, J D Ullman, "Design and Analysis of Algorithms", Addison-Wesley
Publishing.
3. Algorithm Design, by J. Kleinberg and E. Tardos, Addison-Wesley, 2005.
4. Algorithms, by S. Dasgupta, C. Papadimitriou, and U. Vazirani, McGraw-Hill, 2006.
SEMESTER-III
Credits
L T P C
CSE 201 L Design and Analysis of Algorithms Lab C 0 0 2 1

1. Any start up programs to teach C++ language.
2. Any start up programs to teach C++ language. Discuss linked lists and Hash table as a set of
liked lists.
3. Programs for summation of series 1+X+X^2+X^3+…with different time complexities.
Any other example of solving a problem with different time complexity programs.
4. Any two sorting techniques with time complexity analysis
Converting recursive programs to non-recursive programs. Towers of Hanoi Problem example.
5. Binary Search Tree and Heapsort.
6. Fractional Knapsack problem, One to All shortest path (Dijkstra’s algorithm).
7. Minimum spanning tree, Huffman Code.
8. All-to-all shortest paths, Transitive closure of a given directed graph using Warshall’s
algorithm.
9. Implement 0/1 Knapsack problem using Dynamic Programming.
10. Playing cards games simulation (Randomized algorithms), Real life events simulation.
11. Scheduling algorithms (CPU scheduling), Able and Baker problem.
12. Graph Traversal:
a. Print all the nodes reachable from a given starting node in a digraph using BFS
method.
b. Check whether a given graph is connected or not using DFS method.
c. 8 Queens problem, 16-puzzle problem.
13. Approximation algorithms: TSP, Vertex cover, SAT, Set Cover.
14. Any non-polynomial problems and solutions.
15. Simulation of Games and Scheduling problems.
SEMESTER-III
Credits
L T P C
ECE 211 Digital Electronics C 2 1 0 3
UNIT I: DIGITAL FUNDAMENTALS

4 and 5 variable K-maps, 1’s and 2’s complements. Codes – Binary. BCD, Excess 3. Gray,
Alphanumeric codes. Sum of products and product of sums. Min terms and Maxterms. Quine-
McCluskey method of minimization.
UNIT II: COMBINATIONAL CIRCUIT DESIGN

4-bit Adder and Subtractor. Binary Parallel Adder – Carry look ahead adder BCD Adder. Multiplexer.
Demultiplexer. Magnitude Comparator. Decoder. Encoder. Priority Encoder.
UNIT III: SYNCHRONOUS SEQUENTIAL CIRCUITS

Flip flops – SR, JK, T, D, Master/Slave FF – operation and excitation tables. Triggering of FF. Analysis
and design of clocked sequential circuits Design – Moore/Mealy models. State minimization. State
assignment. Circuit implementation – Design of Counters. Ripple Counters-Ring Counters. Shift
Registers. Universal Shift Register.
UNIT IV: ASYNCHRONOUS SEQUENTIAL CIRCUITS

Stable and Unstable states. Output specifications. Cycles and races. State reduction. Race free
assignments. Hazards. Essential Hazards. Pulse mode sequential circuits. Design of Hazard free
circuits.
UNIT V: MEMORY DEVICES

Classification of memories – ROM – ROM organization – PROM – EPROM – EEPROM –EAPROM.
RAM – RAM organization – Write operation – Read operation –Programmable Logic Devices –
Programmable Logic Array (PLA) – Programmable Array Logic (PAL) – Field Programmable Gate
Arrays (FPGA) – Implementation of combinational logic circuits using ROM. PLA. PAL.
1. M. Morris Mano, “Digital Design”, 5th Edition, Pearson Education (Singapore) Pvt. Ltd., New
Delhi, 2014.
2. John F. Wakerly, “Digital Design”, Fourth Edition, Pearson/PHI, 2008.
3. John. M Yarbrough, “Digital Logic Applications and Design”, Thomson Learning, 2006.
4. Charles H. Roth. “Fundamentals of Logic Design”, 6th Edition, Thomson Learning, 2013.
5. Donald P. Leach and Albert Paul Malvino, “Digital Principles and Applications”, 6th Edition,
TMH, 2006.
6. Thomas L. Floyd, “Digital Fundamentals”, 10th Edition, Pearson Education Inc, 2011.
7. Donald D. Givone, “Digital Principles and Design”, TMH, 2003.
SEMESTER-III
Credits
L T P C
ECE 211 L Digital Electronics Lab C 0 0 2 1

1. Realization of Basic Logic Gates.
2. Design of Code Converters (Binary to Gray) & (Gray to Binary).
3. Design of
a. Half-Adder/Subtractor
b. Full-Adder/Subtractor
c. Multiplexers/De Multiplexers
d. ALU Design
4. Design of Decoder and Encoder/ BCD 7SSD.
5. Design of Magnitude Comparator (2-bit).
6. Design and Verification of Flip-Flops using IC.
7. Design of Asynchronous Counter (Any Mod, Up and Down, Jhonson and Ring).
8. Design of Synchronous Counter (Any Mod, Decade counter 74ls90).
9. Design of Universal Shift Register (Serial to Parallel, Parallel to Serial.
10. Serial to Serial and Parallel to Parallel Converters).
11. Design & Verification of Memory (SRAM).
12. FSM Based Design Project.
SEMESTER-III
Credits
L T P C
CSE 106 L Hands on Using Python C 0 0 4 2
Decision Making Control

1. Write a Python program to find the distance between two coordinate points (x1, y1) and (x2,
y2).
2. Write a Python program to input Percentage. Calculate percentage and grade according to
following:
Percentage >= 90% : Grade A
Percentage >= 80% : Grade B
Percentage >= 70% : Grade C
Percentage >= 60% : Grade D
Percentage >= 40% : Grade E
Percentage < 40% : Grade F
3. Write a Python program to find maximum between three numbers.
4. Write a Python program that computes the real roots of a quadratic function. Your program
should begin by prompting the user for the values of a, b and c. Then it should display a message
indicating the nature of real roots, along with the values of the real roots (if any).
5. Write a program to input angles of a triangle and check whether triangle is valid or not. Also,
validate the angles entered by the user. (Sum of the three angles of triangle is 180 )
0
6. Write a program to input basic salary of an employee and calculate its Gross salary according
to following:
Basic Salary <= 10000 : HRA = 20%, DA = 80%
Basic Salary <= 20000 : HRA = 25%, DA = 90%
Basic Salary > 20000 : HRA = 30%, DA = 95%
Looping Control
15. Write a Python program to print the sum of the series 1/2+1/3+1/4+ ... +1/N. Where N is natural
number.
16. Write a Python program that prompts user to enter numbers. The process will repeat until user
enters 0. Finally, the program prints sum of the numbers entered by the user.
17. Write a Python program to print all the numbers from 1 to 1000 that are not divisible by 2, 3,
5, 7, 11, 13, 17 and 19.
18. Write a Python program to find HCF (GCD) of two numbers.
19. Write a Python program to check whether a number is Armstrong number or not.
20. Write a Python program to swap first and last digits of a number.
21. Write a Python program for printing prime numbers up to N. (N>100).
22. Write a Python program to construct the following pattern, using a nested for loop.
*
* *
* * *
* * * *
* * * * *
* * * *
* * *
* *
*
23. Write a Python program to print following matrix.
1 0 1 0
0 1 0 1
1 0 1 0
0 1 0 1
Functions
24. Define a function to find sum of all odd numbers between 1 to n.
25. Define a function to check whether a number is palindrome or not.
26. Define a function to calculate the area of a circle using the formula.
27. Define a function to check whether number is perfect or not.
28. Define a function to print multiplication table of any number.
29. Define a function to print table of a number. Using this function display table of numbers from
1 to 10.
30. Define a recursive function to find power of a number.
31. Define a recursive function count number of digits in a number.
32. Write a recursive function to find a find 1 + 2 + ………..+n .
5 5 5
33. Write a python program to find the factorial value of a number using recursion.
34. Write a python program to implement Tower of Hanoi using recursive function.
35. Write function for finding factors (n) and use factors function to check whether given number
n is prime or not.
36. Write a python program for printing Fibonacci series
a. Write recursive approach implementation
b. Write iterative implementation
Files
37. Write a Python program to copy the content of one file to other file.
38. Write a Python program to number of words in the above txt file.
39. Write a Python program to number of characters without space in the above txt file.
40. Write a program that reads data from a file and print the no of vowels and constants in the file.
41. Write a python program that accept file Name as input from the user. Open the file and count
the number of times a character appears in the file.
List, Tuples and Dictionary
42. Write a Python program to create a list of each digit is a element in a list from a number.
Example: Input: 5467, Output: [5,4,6,7]
43. Write a Python program to form a number from a given list of digits Example: Input: [5, 4, 6,
7], Output: 5467
44. Write a Python program to find the second smallest number and second largest in a list.
45. Write a python program to create dictionary of index is the key and corresponding prime
number as value up to 100. Output: {1:2, 2:3, 3:5, 4:7, 5:11, 6:13, 7:17, 8:19 ……. and soon }
46. Write a Python program to find the smallest value and largest value in a dictionary.
47. Example: Input: D1={1:200,2:3000,3:100,5:20} output: 20, 3000.
48. Write a Python script to generate and print a dictionary that contains a number (between 1
and n) in the form (x, x*x).
Sample Dictionary ( n = 5) :
Expected Output : {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}
49. Write a Python program to convert a list of characters into a string. Example: Input:
[‘s’,’t’,’r’,’i’,’n’,’g’], Output: string.
50. Write a Python program to combine two dictionary adding values for common keys.
d1 = {'a': 10, 'b': 20, 'c':30}
d2 = {'a': 30, 'b': 20, 'd':40}
Sample output: {'a': 40, 'b': 40, 'd': 40, 'c': 30}
51. Write a program to print index at which a particular value exists. If the value exists a multiple
location in the list, then print all the indices. Also, count the number of times the value is
repeated in the list.
52. Write a program to remove all duplicate elements in a list.
53. Write a program to create a list of numbers in the range 1 to 10. Then delete all the odd numbers
from the list and print the final list.
Strings
54. Write a program that counts up the number of vowels contained in the string S. Valid vowels
are: 'a', 'e', 'i', 'o', and 'u'. For example, if s = 'azcbobobegghakl', your program should print:
number of vowels 5
55. Assume s is a string of lower-case characters. Write a program that prints the number of times
the string 'bob' occurs in s. For example, if s = 'azcbobobegghakl', then your program should
print Number of times bob occurs is 2.
56. Write a Python program that finds whether a given character is present in a string or not. In
case if it is present then it prints the index at which it is present. Do not use built-in find
functions to search the character.
57. Write a Python program that counts the occurrence of a character in a string. Do not use built-
in function.
58. Write a python program for following:
a. Take a input string with spaces, split it into list of words
b. From the list of words, create dictionary with keys (only unique words) and values
(length of the word)
59. Write a python program to count number of vowels, spaces and to find longest word in a given
input string. (Take input string with spaces)
60. Write a python program to reverse a string. Do not use inbuilt function.
Searching and Sorting
61. Write a Python program for binary search algorithm.
62. Write a Python program for linear search algorithm.
63. Write a Python program to display the elements in an ascending order using bubble sort
algorithm.
64. Write a Python program to display the elements in a descending order using selection sort
algorithm.
Object Oriented Programming
65. Write a Python program to create a student class (id, Name, mid1_marks, mid2_marks,
quiz_marks). Create a student objects and write a function marksList() to display student’s
result as given below:
ROLL NUMBER:
NAME:
MID1:
MID2:
QUIZ:
TOTAL: MID1+MID2+QUIZ
RESULT: A GRADE (IF TOTAL>=80), B GRADE (TOTAL<80 and TOTAL>=60), C
GRADE (TOTAL>=50 and TOTAL<60)
(Assume that maximum marks for mid_term1 and mid2_marks is 25 each , and
quiz_marks is 50).
66. Write a Python program to create a EMP class (id, Name, sal), create employee objects and
write a function PaySlip(empobj) to display particular employee Pay Slip as given below:
EMP ID:
EMP NAME:
EMP BASIC: It is equal to sal.
EMP HRA:
EMP DA:
EMP TAX:
EMP GROSS SAL: BASIC (sal) +HRA (18% of sal) +DA (10% of sal)
EMP NET SAL: GROSS SAL-10% of GROSS SAL
67. Write a Python program to define rectangle class with field’s length and breadth. Define color
rectangle class which is inherited from rectangle class with additional field color. Create N
color rectangle objects and print which color rectangle is having minimum area.
68. Write a Python program to define CAR class (model, speed, price) and Firing CAR class which
inherits from CAR with additional field number of bullets and fire method ().
69. Write a Program in python using object-oriented concept to create a base class called Polygon
and there are three derived classes Named as triangle, rectangle and square.
70. The base class consists of the input function for accepting sides length
71. The derived classes must have output function for displaying area of triangle, rectangle and
square.
SEMESTER-III
Credits
L T P C
CSE 231 Industry Standard Coding Practice -II ES 0 0 4 1
UNIT-I
Problem solving using Stacks, Coding solutions for the implementation of stack using an array, Coding
solutions for the implementation of stack using a linked list, Problem solving on expression conversion
and evaluations, Examples, Practice Problems.
UNIT-II
Search operations implementing linear/binary search, Bubble Sort, Selection Sort, Insertion Sort,
Evaluation of sorting Algorithms. Problem solving using Quick Sort, Merge Sort, O(n log n)
algorithms, Examples, Practice problems.
UNIT-III
Problem solving approaches using Non-linear data structures, Coding problems on the height of a
binary tree, Size of a binary tree, Tree order traversals, Problem Solving on Binary Trees, Problems
solving on key search on binary search trees, Time comparison and analysis on Binary Search Trees,
Coding on a binary search tree problems, Search/probe sequence validation, Examples, Practice
problems.
UNIT-IV
Industry Standards of leveraging DBMS concepts: SQL Queries, Entity Relationship Models,
Question and answers, Query Optimization, Transactions & Concurrency, Normalization, case studies,
Question and answers Examples, Practice problems.
UNIT-V
Problem solving approaches with problem setter’s mind set, Creating edge cases, Constraints for the
test cases, I/O Faults, Examples, Practice problems. Problem solving Methods and techniques:
Encoding methods, Handling faults within the code, Examples, Practice problems. Push a branch to
GitHub, creating a pull request, Merging a pull request, Get back the changes from Github, Examples,
Practice Questions.
SEMESTER-III
Credits
L T P C
ECO 121 Principles of Economics HS 3 0 0 3
UNIT I: INTRODUCTION TO ECONOMICS

Why study economics? Scope and method of economics; the economic problem: scarcity and choice;
the question of what to produce, how to produce and how to distribute output. Science of economics;
the basic competitive model; prices. Science of economics; the basic competitive model; prices.
Property rights and profits; incentives and information; rationing. Opportunity sets; economic systems;
reading and working with graphs.
UNIT II: DEMAND AND SUPPLY

Determinants of individual demand/supply; demand/supply schedule and demand/supply curve;
market versus individual demand/supply. Shifts in the demand/supply curve, demand, and supply
together. How prices allocate resources, elasticity, and its application. How prices allocate resources,
elasticity, and its application. Controls on prices; taxes and the costs of taxation. Consumer surplus;
producer surplus and the efficiency of the markets.
UNIT III: CONSUMER THEORY

The consumption decision - budget constraint. The consumption decision - budget constraint,
consumption, and income/price changes. Demand for all other goods and price changes. M\references
(indifference curves); properties of indifference curves. Utility and preferences (indifference curves);
properties of indifference curves. Consumer ‘s optimum choice. Income and substitution effects.
Income and substitution effects. Applying consumer theory: Labour.
UNIT IV: PRODUCER THEORY

Production, short- run production function and returns to factor. Production, short- run production
function and returns to factor. Production, short- run production function and returns to factor.
Average-marginal relationship. Long– run production function and laws of return to scale- role of
technology. Long– run production function and laws of return to scale- role of technology. Cost
function and cost structure of a firm in the short- run. Long run cost function and cost structure.
UNIT V: TYPES OF MARKET

Perfect competition -features. Perfect competition- profit maximization. Shut-down and break-even
points. Monopoly: marginal revenue; marginal cost; profit maximization. Shutdown rule; market
power; price discrimination. Monopolistic competition and product differentiation
TEXTBOOKS
1. Principles of microeconomics, N. Gregory Mankiw, Publisher: Cengage Learning
5th edition.
2. Perloff, Jeffrey M. Microeconomics. 5th ed. Addison Wesley, 2008. ISBN: 9780321558497.
SEMESTER-III
Credits
L T P C
ISES 201 Industry Specific Employability Skills-III HS 1 1 0 1
UNIT I: QUANTS
Numbers, Problems on numbers (Divisibility, power cycle, reminder cycle), Problems on ages,
Problems on HCF and LCM, Simple interest, compound interest, Data interpretation (Charts, tables,
pie charts, lines).
UNIT II: REASONING

Direction sense, Direction sense, Logical order, Analytical reasoning, Passage and inference, Selection
decision table, Attention to details, Seating arrangements
UNIT III: VERBAL

Spellings, Selecting words, Spotting errors, Ordering of words, Sentence correction, Sentence
improvement, Synonyms, Antonyms.

Topic wise discussion, Group discussion, Debate, Presentations.
Perspective.
Students.
SEMESTER - IV
SEMESTER-IV
Credits
L T P C
MAT 221 Probability and Statistics for Engineers ES 3 0 0 3
UNIT I: INTRODUCTION TO PROBABILITY

Introduction, counting and set, terminologies and examples, conditional probability, independence and
Bayes’ theorem.
UNITII: PARTIAL DERIVATIVES

Discrete random variables, variance of discrete random variables, continuous random variables,
Expectation, variance and standard deviation of continuous random variables, central limit theorem
and law of large numbers, joint distributions and independence, covariance, and correlation.
UNIT III: BAYESIAN INFERENCE

Introduction to statistics, Maximum likelihood estimate, Bayesian updating discrete priors,
probabilistic prediction, odds, continuous priors; Beta distribution, conjugate priors, probability
intervals.
UNIT IV: NULL HYPOTHESIS SIGNIFICANCE TESTING

The frequentist school of statistics, Null hypothesis significant testing, comparison between frequentist
and Bayesian inference.
UNIT V: CONFIDENCE INTERVALS AND REGRESIONS

Confidence intervals: normal data, three views, mean of the non-normal data; Bootstrap confidence
intervals, linear regression.
TEXTBOOKS
1. J. Jacod and P. Protter, Probability Essentials, Springer, 2004.
2. K. S. Trivedi, Probability and Statistics with Reliability, Queuing, and Computer Science
Applications, Wiley India, 2008.
REFERENCES
1. S. Ross, A First Course in Probability, 6th Edn., Pearson, 2002.
SEMESTER-IV
Credits
L T P C
MAT 131 Differential Equations BS 3 0 0 3
UNIT I: FIRST ORDER DIFFERENTIAL EQUATIONS

Geometric meaning of 𝑦 ′ = 𝑓(𝑥, 𝑦), Direction Fields, Euler’s Method, Classification of ODEs (Linear,
Non-linear, Exact, Separable), Integrating Factor, Bernoulli Equations, Initial Value Problem,
Modelling (Free falling object, Radioactivity, RL-circuit).
UNIT II: SECOND AND HIGHER ORDER LINEAR ODES

Homogeneous Linear ODEs, Modelling of Free Oscillations of a Mass-Spring System, Euler-Cauchy
Equations, Non-homogeneous ODEs, Variation of Parameters, Modelling (Forced Oscillations,
Electric Circuits).
UNIT III: SYSTEM OF ODES

Modelling Engineering problems (Electric Network, Mixing problem in two tanks etc.) as systems of
ODEs, Wronskian, Phase-Plane Method, Critical Points & Stability, Qualitative Methods for
Nonlinear Systems, Nonhomogeneous Linear Systems of ODEs.
UNIT IV: SERIES SOLUTIONS OF ODES

Introduction to power series method, Legendre’s equation & polynomials, Frobenius Method, Bessel’s
Equations & Functions.
UNIT V: LAPLACE TRANSFORMS

Laplace Transforms: Laplace transforms of standard functions, Shifting Theorems, Transforms of
derivatives and integrals, Unit step function, Dirac’s delta function, Inverse Laplace transforms,
Convolution theorem (without proof). Application: Solutions of ordinary differential equations using
Laplace transforms.
TEXTBOOKS
1. Erwin Kreyszig, Advanced Engineering Mathematics, 10th Edition, Wiley-India.
REFERENCES
1. Mary L. Boas, Mathematical Methods in Physical Sciences, 3rd Edition, Wiley-India.
2. G. F. Simmons, Differential Equation with Applications and Historical Notes, TATA McGraw
Hill.
3. S. Vaidyanathan, Advanced Applicable Engineering Mathematics, CBS Publishers.
SEMESTER-IV
Credits
L T P C
CSE 204 Computer Organization and Architecture C 3 0 0 3
UNIT I: BASIC STRUCTURE OF COMPUTERS

Functional units – Bus structures – Instruction set architecture: Instruction formats - addressing modes
- Architecture and instruction set of 8086/8088 microprocessor- Assembly language programming -
Fixed point and floating-point operations – ALU design.
UNIT II: BASIC PROCESSING UNIT

Fundamental concepts – Execution of a complete instruction – Hardwired control – Micro
programmed control design- Nano programming- CISC-RISC- principles.
UNIT III: PIPELINE PROCESSING

Basic concepts, instruction and arithmetic pipeline, data hazards, control hazards and structural
hazards, techniques for handling hazards. Pipeline optimization techniques: Compiler
techniques for improving performance.
UNIT IV: MEMORY SYSTEM

Basic concepts – Semiconductor RAM – ROM – Speed – Size and cost – Cache memories –
Improving cache performance – Virtual memory – Memory management requirements–
Associative Memories-Secondary-storage-devices.
UNIT V: I/O ORGANIZATION

Accessing I/O devices – Programmed Input/output - Interrupts – Direct Memory Access–
Interface circuits – Standard I/O Interfaces - I/ O devices and Processors.
TEXTBOOKS
1. Computer Organization, Carl Hamacher, Zvonko Vranesic and Safwat Zaky, V Edition,
McGraw-Hill publications.
2. “Computer Organization and Architecture – Designing for Performance”, William
Stallings, Ninth edition, Pearson publications.
REFERENCES
1. Computer System Architecture, Morris Mano, Third edition, Pearson publications.
2. Andrew S. Tanenbaum, “Structured Computer Organization”,
3. David A. Patterson and John L. Hennessy, “Computer Organization and Design: The
Hardware/Software interface”
4. John P. Hayes, “Computer Architecture and Organization”, Third Edition, Tata
McGraw Hill.
5. An Introduction to 8086/8088 Assembly Language Programming, Thomas P. Skinner,
John Wiley & Sons, 1985.
SEMESTER-IV
Credits
L T P C
CSE 204 L Computer Organization and Architecture Lab C 0 0 2 1

1. Write Assembly language program to print the numbers from 0 to 9.
2. Write Assembly language programs to find average of numbers stored in an array.
3. Write Assembly language programs to find the largest number in an array.
4. Write Assembly language programs to sort the numbers in ascending order.
5. Write Assembly language programs to find L.C.M of two numbers.
6. Write Assembly language programs to find G.C.D of two numbers.
7. Write Assembly language programs to display nth term Fibonacci number.
8. Write Assembly language programs to find the factorial of a number.
9. Programs for 16-bit Arithmetic Operations for 8086 (Using Microprocessor trainer kit 8086).
10. Program for String Manipulations for 8086 (Using Microprocessor trainer kit 8086).
11. Develop an assembler to convert the given assembly language program into machine
language program by considering 8086/88 microprocessor.
12. Develop a simulator for 8086/88 microprocessor.
SEMESTER-IV
Credits
L T P C
CSE 301 Operating Systems C 3 0 0 3
UNIT I: OPERATING SYSTEMS OVERVIEW

Operating system overview-objectives and functions, Evolution of Operating System- Computer
System Organization- Operating System Structure and Operations- System Calls, System
Programs, OS Generation and System Boot.
UNIT II: PROCESS SCHEDULING

Processes-Process Concept, Process Scheduling, Operations on Processes, Inter process
Communication; CPU Scheduling algorithms; OS – examples.
UNIT III: PROCESS SYNCHRONIZATION AND DEADLOCKS

Threads- Overview, Multithreading Models; Process Synchronization – Critical Section Problem,
Mutex Locks, Semaphores, Monitors; Deadlocks- OS examples.
UNIT IV: STORAGE MANAGEMENT

Main Memory-Contiguous Memory Allocation, Segmentation, Paging, Virtual Memory- Demand
Paging, Page Replacement, Allocation, Thrashing; OS examples.
UNIT V: STORAGE MANAGEMENT

I/OSYSTEMS: Mass Storage Structure- Overview, Disk Scheduling and Management; File System
Storage-File Concepts, Directory and Disk Structure, Sharing and Protection; File System
Implementation- File System Structure, Directory Structure, Allocation Methods, Free Space
Management- OS examples.
TEXTBOOKS
1. Abraham Silberschatz, Peter Baer Galvin and Greg Gagne, “Operating System Concepts”, 9th
Edition, John Wiley and Sons Inc.
REFERENCES
1. William Stallings, “Operating Systems – Internals and Design Principles”, 9th Edition, Pearson
publications.
2. Andrew S. Tanenbaum, “Modern Operating Systems”, Fourth Edition, Pearson publications.
3. Harvey M. Deitel, Paul J. Deitel, David R. Choffnes (Author)“Operating Systems”, Third
Edition.
SEMESTER-IV
Credits
L T P C
CSE 301 L Operating Systems Lab C 0 0 2 1

Shell Programs
1. Write a script to find the greatest of three numbers (numbers passed as command line
parameters).
2. Write a script to check whether the given no. is even/odd.
3. Write a script to calculate the average of n numbers.
4. Write a script to check whether the given number is prime or not.
5. Write a script to check whether the given input is a number or a string.
6. Write a script to compute no. of characters and words in each line of given file.
7. Write a script to print the Fibonacci series up to n terms.
8. Write a script to calculate the factorial of a given number.
9. Write a script to calculate the sum of digits of the given number.
10. Write a script to check whether the given string is a palindrome.
11. Write a shell script that accepts a string from the terminal and echo a suitable message if it
doesn’t have at least 5 characters including the other symbols.
12. Write a shell script to echo the string length of the given string as argument.
13. Write a shell script that accepts two directory Names as arguments and deletes those files in
the first directory which are similarly Named in the second directly. Note: Contents should also
match inside the files.
14. Write a shell script to display the processes running on the system for every 30 seconds, but
only for 3 times.
15. Write a shell script that displays the last modification time of any file.
16. Write a shell script to check the spellings of any text document given as an argument.
17. Write a shell script to encrypt any text file.
18. Combine the above commands in a shell script so that you have a small program for extracting
a wordlist.
19. Write a shell script which reads the contents in a text file and removes all the blank spaces in
them and redirects the output to a file.
20. Write a shell script that changes the Name of the files passed as arguments to lowercase.
21. Write a shell script to translate all the characters to lower case in a given text file.
22. Write a shell script to combine any three text files into a single file (append them in the order
as they appear in the arguments) and display the word count.
23. Write a shell script that, given a file Name as the argument will write the even numbered line
to a file with Name evenfile and odd numbered lines to a file called oddfile.
24. Write a shell script which deletes all the even numbered lines in a text file.
25. Write a script called hello which outputs the following: • your userName • the time and date •
who is logged on • also output a line of asterices (*********) after each section.
26. Write a script that will count the number of files in each of your subdirectories.
27. Write a shell script like a more command. It asks the user Name, the Name of the file on
command prompt and displays only the 15 lines of the file at a time on the screen. Further, next
15 lines will be displayed only when the user presses the enter key / any other key.
28. Write a shell script that counts English language articles (a, an, the) in a given text file.
29. Write the shell script which will replace each occurrence of character c with the characters chr
in a string s. It should also display the number of replacements.
30. Write a shell program to concatenate to two strings given as input and display the resultant
string along with its string length. Write a shell program to simulate a simple calculator. 90)
Write a shell program to count the following in a text file. • Number of vowels in a given text
file. • Number of blank spaces. • Number of characters. • Number of symbols. • Number of
lines
CPU scheduling algorithms
• First Come First Serve
• Shortest Job First
• Priority
• Round Robin
Semaphore and Deadlock
• write a C program to implement the Producer & consumer Problem using Semaphore.
• Write a C program to simulate Bankers algorithm for the purpose of deadlock avoidance.
Page Replacement Algorithms
• First In First Out
• Least Recently Used
• Optimal
• Least Frequently Used
• Second Chance
SEMESTER-IV
Credits
L T P C
CSE 207 Java Programming C 3 0 0 3
UNIT I: INTRODUCTION TO JAVA

An Overview of Java - Data types, Variables and Arrays, operators, expressions, Control statements,
Classes, Objects, Constructor, Methods, this reference, static keyword, and final keyword; String
handling, Compiling using command line argument; Inheritance - Concept, Member access, Abstract
Class, Interface, Creating Multilevel hierarchy- super uses, Packages-access specifiers, using final with
inheritance; Polymorphism - Compile time Polymorphism, Method overloading, Constructor
overloading; Run time polymorphism, Method overriding, Dynamic method dispatch.
UNIT II: EXCEPTION HANDLING & MULTITHREADING

Fundamentals of exception handling, Uncaught exceptions, using try and catch, multiple catch blocks,
Exception types - Introduction to Object class, Exception class hierarchy, Termination or presumptive
models, Built-in exceptions, User defined exceptions, Nested try statements, Throw, Throws, and
Finally. Multithreading- Differences between thread-based multitasking and process-
based multitasking, Java thread model, Thread life cycle, Creating threads – Thread class, Runnable
interface, Thread priorities, Synchronizing threads, Inter-thread communication.
UNIT III: STREAM BASED I/O (JAVA.IO)

Java API, The Stream Classes-Byte streams and Character streams, reading console Input and Writing
Console Output, File class, Reading and writing Files, Random access file operations, The Console
class, Serialization, Enumerations, auto boxing, generics.
UNIT IV: THE COLLECTIONS FRAMEWORK (JAVA.UTIL) & JDBC

Collection’s overview, Collection Interfaces, The Collection classes- Array List, Linked List, Hash
Set, Tree Set, Priority Queue, Array Deque, and other utility classes. Accessing a Collection via an
Iterator, using an Iterator, The For-Each alternative, Map Interfaces and Classes, Comparators,
Collection algorithms, String Tokenizer. JDBC – What is database, Table, SQL Syntax-Create, Insert,
Select, Drop, Alter, Update, Delete, what is JDBC, JDBC Architecture and Components, JDBC Driver
Types, Connections, Statements, Result Set.
UNIT V: GUI PROGRAMMING WITH SWING

Introduction - AWT & Swings, MVC architecture, components, containers. Understanding Layout
Managers, Flow Layout, Border Layout, Grid Layout, Card Layout, Grid Bag Layout. Event
Handling- The Delegation event model- Events, Event sources, Event Listeners, Event classes,
Handling mouse and keyboard events, Adapter classes, Inner classes, Anonymous Inner classes. A
Simple Swing Application, Applets – Applets and HTML, Security Issues, Applets and Applications,
passing parameters to applets. Creating a Swing Applet, painting in Swing, A Paint example, Exploring
Swing Controls- J Label and Image Icon, J Text Field, The Swing Buttons- J Button, J Toggle Button,
J Check Box, J Radio Button, J Tabbed Pane, J Scroll Pane, J List, J Combo Box, Swing Menus,
Dialogs.
TEXTBOOKS
1. Java The complete reference, 11th edition, Herbert Schildt, McGraw Hill
Education (India) Pvt. Ltd.
REFERENCES
1. Understanding Object-Oriented Programming with Java, updated edition, T.
Budd, Pearson Education.
2. An Introduction to programming and OO design using Java, J. Nino and F.A.
Hosch, John Wiley & sons.
3. Introduction to Java programming, Y. Daniel Liang, Pearson Education.
4. Object Oriented Programming through Java, P. Radha Krishna, and Universities
Press.
5. Programming in Java, S. Malhotra, S. Chaudhary, 2nd edition, Oxford Univ. Press.
6. Java Programming and Object-Oriented Application Development, R. A.
Johnson, Cengage Learning.
SEMESTER-IV
Credits
L T P C
CSE 207 L Java Programming Lab C 0 0 2 1

1. Declare a class Named Teacher. The class will have all the data members as per your convenient.
The class will have constructors. Write a function to read the values of the class variables. The values
of the variable will be stored in a FILE (text file). The values will be stored in a structured format of
your own choice.
Further, read the content of the FILE and display the content in an ordered form (First Name, Last
Name).
Concept Learning:
1. FILE manipulation
2. Use try catch blocks
3. Use multiple try catch block
4. Finally statement
Try to have your own Exception
2. Create three classes Named Student, Teacher, Parents. Student and Teacher class inherits Thread
class and Parent class implements Runnable interface. These three classes have run methods with
statements. The task of the teacher class of the first assignment has to be synchronized. Similarly, the
other two classes should have run methods with few valid statements under synchronized.
3. Create two classes Named Student and Teacher with required data members. Assume that the
information about the Student and Teacher is stored in a text file. Read n and m number of Student
and Teacher information from the File. Store the information in Array list of type Student and Teacher
Array List<Student> and Array List<Teacher>. Print the information of Teacher who taught OOPS
and Maths. Use Iterator and other functions of util in your program.
4. Watch any of the favorite movie of your choice (any language is fine, preferably English). Create a
Text file to store at least 10 meaningful dialogs from the movie and store it in a text file. Process the
file to remove the stop words (eg. the, is, was, …….) and create another file to have clean text (word).
5. Write a java program to create Hashtable to act as a dictionary for the word collection. The dictionary
meaning of the words, including synonyms, etc., has to be displayed.
6. Declare two classes Student and Teacher. The classes will have the data members and constructors
as per your convenience. Write a JAVA program, (i) where the Teacher will enter the marks of the all
the students in the database. (ii) Once the marks are entered, the student can view the marks.
7. Create GUI for the above program to upload the dialog FILE, clean the FILE. The GUI should take
input from the user for invoking the dictionary for displaying dictionary meaning.
The class will have constructors. Develop a GUI to read the values of the class variables from the
keyboard. Use text field to read the values. Use button to store it in a file one by one. The values will
be stored in a structured format of your own choice.
Have an option in the GUI to search the Name of the students by roll number and display the content
in the test field.
9. Create two classes Named Student and Teacher with required data members. Read the information
about the student and teacher using text fields. Use checkbox to choose the option to feed either teacher
information or student information. Store the information about the Student and Teacher in a text file.
Read n and m number of Student and Teacher information from the File. Show in the GUI about a
Teacher who taught two subjects to a section. Develop at least one of the applications (AWT problem)
using swing package.
10. Create a Window based applications using various controls to handle subject registration for
exams. Have a List Box to display the subject of semesters. Have one more List box having subject
codes. Have a combo box to select the Semester, which will change the list of course and code in the
list boxes. Display the subject registered for the examination on the right side of the window.
The class will have constructors. Develop a GUI to read the values of the class variables from the
keyboard. Use text field to read the values. Use button to store it in a file one by one. The values will
be stored in a structured format of your own choice.
Have an option in the GUI to search the Name of the students by roll number and display the content
in the test field. Develop at least one of the applications (AWT problem) using swing package.
12. Create a Window based application for displaying your photo album. Create a Frame and Canvas.
Change the border, foreground and background colors of canvas and other controls. Have buttons to
start the image show, pause the image show and end the image show. Explore the options to play
background music.
13. Create a Window application with menu bar and menu. The frame will also have a text area with
scroll bar. In the menu, have File related options. Open a file and its content has to be displayed in the
text area.
14. Create a GUI using various controls: (i) to upload the marks of all the students presented in a
marks.csv or marks.txt file into the database. (ii) to show the marks of the respective student after
uploading the marks into the database. Note: Handle the exception, if the file is not present (or) if the
marks are not uploaded in the database.
15. Individual Project. Every student should do a project to achieve all the course outcomes. Based on
the course outcomes, the project will be evaluated.
SEMSTER-IV
Credits
L T P C
CSE 203 Formal Languages and Automata Theory C 3 0 0 3
UNIT I: FUNDAMENTALS
Strings, Alphabet, Language, Operations, Finite state machine, definitions, finite automaton model,
acceptance of strings, and languages, deterministic finite automaton and non-deterministic finite
automaton, transition diagrams and Language recognizers.
Finite Automata: NFA with Î transitions - Significance, acceptance of languages. Conversions
and Equivalence: Equivalence between NFA with and without Î transitions, NFA to DFA
conversion, minimisation of FSM, equivalence between two FSM’s, Finite Automata with output-
Moore and Melay machines.
UNIT II: REGULAR LANGUAGES

Regular sets, regular expressions, identity rules, constructing finite Automata for a given regular
expressions, Conversion of Finite Automata to Regular expressions. Pumping lemma of regular sets,
closure properties of regular sets (proofs not required).
Grammar Formalism: Regular grammars-right linear and left linear grammars, equivalence
between regular linear grammar and FA, inter conversion, Context free grammar, derivation trees,
sentential forms. Right most and leftmost derivation of strings.
UNIT III: CONTEXT FREE GRAMMARS

Ambiguity in context free grammars. Minimisation of Context Free Grammars. Chomsky normal
form, Greiback normal form, Pumping Lemma for Context Free Languages. Enumeration of properties
of CFL (proofs omitted). Push Down Automata: Push down automata, definition, model, acceptance
of CFL, Acceptance by final state and acceptance by empty state and its equivalence. Equivalence of
CFL and PDA, interconversion. (Proofs not required). Introduction to DCFL and DPDA.
UNIT IV: TURING MACHINE

Turing Machine, definition, model, design of TM, Computable functions, recursively enumerable
languages. Church’s hypothesis, counter machine, types of Turing machines (proofs not required).
linear bounded automata and context sensitive language.
UNIT V: COMPUTABILITY THEORY

Chomsky hierarchy of languages, linear bounded automata and context sensitive language, LR(0)
grammar, decidability of, problems, Universal Turing Machine, undecidability of posts.
Correspondence problem, Turing reducibility, Definition of P and NP problems, NP complete and NP
hard problems.
TEXTBOOKS
1. “Introduction to Automata Theory Languages and Computation”. Hopcroft H.E. and
Ullman J. D. Pearson Education
2. Introduction to Theory of Computation – Sipser 2nd edition Thomson
REFERENCES
1. Introduction to Forml languages Automata Theory and Computation Kamala Krithivasan
Rama R.
2. Introduction to Computer Theory, Daniel I.A. Cohen, John Wiley.
3. Theory Of Computation: A Problem - Solving Approach, Kavi Mahesh, Wiley India Pvt.
Ltd.
SEMESTER-IV
Credits
L T P C
ISES 202 Industry Specific Employability Skills-IV HS 1 1 0 1
UNIT I: QUANTS
Logarithms. Permutations and combinations. Probability. Progressions, Geometry and Mensuration,
Geometry and Mensuration
UNIT II: REASONING

Statement and conclusions, Most logical choice, Inferred meaning, Data arrangements, Venn
diagram, Flow charts and logical gates, Puzzles, Case lets, Ordering, Ranking, Grouping.
UNIT III: VERBAL

Classification of sentences, Logical sequence of words, Verbal reasoning Analyzing arguments,
Verification of truth, Matching definitions, Theme detection, Idioms and phrases Antonyms Synonyms

Conditionals, Tense Forms, Verb Forms.
UNIT V: VERBAL ABILITY

Extempore, JAM, Active listening, Email Etiquette, Self-image and self-presentation, FAQ’s, Resume
Perspective.
Students.
SEMESTER-IV
Credits
L T P C
CSE 233 Industry Standard Coding Practice - III ES 0 0 4 1
UNIT-I
Introduction to Python, Basic syntax, variables and data types, operators, Input and Output, conditional
statements and loops, Problem solving on accessing strings, string operations, string slices, functions
and methods, Introduction to lists, accessing list, working on Lists, Matrix data, Practice Problems.
UNIT-II
Introduction to tuple, accessing tuples, tuple operations, introduction to dictionaries, accessing values
in dictionaries, properties and functions, importing modules, math module, random module, packages
and composition, Problem solving through user defined functions and methods, implementing
exception handling, except clause, try? finally clause, user defined exceptions, Advanced data types,
examples, Practice problems.
UNIT-III
Problem Solving through Class and Instance Attributes - Properties vs. getters and setters -
Implementing a Property Decorator, Descriptors, Inheritance, Multiple Inheritance, Multiple
Inheritance Example, Magic Methods and Operator Overloading, Callable and Callable Instances,
Inheritance, Python Class for Polynomial Functions.
Problem solving using STL Components: Algorithms - Containers: vector, list, dequeue, arrays,
forward_list, - Container Adaptors: Queue, Priority_queue, Stack – Associative Containers: Set,
Multiset, map, Multimap – Function Objects – Iterators.
Version control systems, Adding new files to the repository, Staging the environment, Commit,
Examples, Practice problems.
UNIT-IV
Industry Standards of leveraging DBMS concepts: Implementing stored procedures, implementing
functions, implementing triggers, implementing transactions, case studies, Question and answers.
UNIT-V
Industry Standards of leveraging DBMS concepts: Understanding Managed code, creating managed
database objects, HTTP Endpoints and Implementation, case studies, Question and answers.
SEMESTER - V
SEMESTER-V
Credits
L T P C
MAT 211 Linear Algebra BS 3 0 0 3
UNIT I: VECTOR SPACE

Elimination, LU factorization, null-spaces and other subspaces, bases and dimensions, vector spaces,
complexity.
UNIT II: FACTORIZATION

Orthogonality, projections, least-squares, QR, Gram–Schmidt, orthogonal functions.
UNIT III: MATRICES

Eigenvectors, determinants, similar matrices, Markov matrices, ODEs, symmetric matrices, definite
matrices.
UNIT IV: ITERATIVE METHODS

Defective matrices, SVD and principal-components analysis, sparse matrices and iterative methods,
complex matrices, symmetric linear operators on functions.
UNIT V: APPLICATIONS
Matrices from graphs and engineering.
TEXTBOOKS
1. G. Strang, Linear Algebra and Its applications, Nelson Engineering, 4th Edn., 2007.
2. K. Hoffman and R. Kunze, Linear Algebra, Prentice Hall of India, 1996.
REFERENCES
1. S. Axler, Linear Algebra Done Right, 2nd Edn., UTM, Springer, Indian edition, 2010.
2. G. Schay, Introduction to Linear Algebra, Narosa, 1997.
SEMESTER-V
Credits
L T P C
CSE 303 Computer Networks C 3 0 0 3
UNIT I: OVERVIEW OF THE INTERNET (PHYSICAL LAYER AND DATA LINK LAYER)
Basic Computer Network concepts, Protocol, Layering Scenario. Layer Architecture: OSI Model,
TCP/IP model. Internet history standards and administration; Comparison of the OSI and TCP/IP
reference model. Guided transmission media, wireless transmission media. Different LAN topologies:
BUS, RING and STAR topology. Data Link layer design issues: Error detection techniques. Error
Correction Techniques, Flow control. Sliding Window protocols. Go back N and selective Repeat
protocols. Difference between single bit sliding window and n-bit sliding window protocols.
UNIT II: MEDIUM ACCESS CONTROL

Static and Dynamic channel Allocations. Shared channel Access: Pure ALOHA and slotted ALOHA.
Persistent CSMA protocols: 1, P and Non-persistent CSMA protocols. CSMA with collision detection.
Comparison of different CSMA protocols. Collision free protocols: Bit-map protocol, Token Ring and
Binary Count down protocols. Limited Contention protocols: Adaptive tree walk protocol. Shared
medium for wireless networks: CSMA/CA or MACA. Interconnecting LANs: HUBS, Repeaters and
Switches and bridges. Spanning tree algorithm for bridges.
UNIT III: NETWORK LAYER

Overview: Connection oriented and connection less services. Comparison of packet switched, and
circuit switched networks. Routing: proactive routing and reactive routing protocols, static and
dynamic routing protocols. Dijkstra Algorithm, Distance vector routing and Link state routing
protocols. Routing in wireless networks: AODV and DSR routing protocols. Overview of IP header
and IP addressing. Classful IP addressing: Class A, B, C, D and E. Limitations of classful Addressing,
Introduction to Subnet. Overview of Congestion: Warning Bit, Choke packets, Load Shedding, RED
(Random Early Detection).
UNIT IV: INTERNETWORKING AND TRANSPORT LAYER

IP Encapsulation and Tunneling. IP packet fragmentation, ICMP, ARP. ICMP, DHCP, Introduction to
Transport layer. Different end-to-end transport layer protocols: TCP and UDP. Brief explanation of
TCP protocol. Packet formats for TCP and UDP protocol.
UNIT V: TRANSPORT AND APPLICATION PROTOCOLS

TCP Connection Management Modeling. TCP Sliding Window. TCP congestion control. Introduction
to application layer paradigms. Client Server model. Introduction and overview of HTTP protocol.
Overview of FTP protocol. Operation of Electronic Mail. Introduction to peer-to-peer communication
models. Introduction and overview of TELNET. Importance of Security in computer Networks.
TEXTBOOKS
1. Computer Networks - Andrew S Tanenbaum, 4th Edition, Pearson Education.
2. Data Communications and Networking - Behrouz A. Forouzan, Fifth Edition TMH, 2013.
REFERENCES
1. Computer Networking: A Top-Down Approach Featuring the Internet, James F. Kurose, K. W.
Ross, 3rd Edition, Pearson Education.
2. Understanding communications and Networks, 3rd Edition, W. A. Shay, Cengage Learning.
SEMESTER-V
Credits
L T P C
CSE 303 L Computer Networks Lab C 0 0 2 1

1. Explain about wire shark and display how to send packets or packets from one layer to
another.
2. Write a Java program to implement Error Detection Technique using CRC Algorithm.
3. Write a Java program to implement Error Correction Technique using Hamming code.
4. Write a Java program to implement TCP Client Server programming.
5. Write a Java program to implement UDP Client Server Programming.
6. Write a Java program to implement 1-bit Stop and Wait Protocol at data link layer.
7. Write a Java program to implement N-bit Sliding Window Protocol at data link layer.
8. Write a Java program to implement Dijkstra Shortest path routing protocol.
9. Write a Java program to implement Distance Vector Routing.
10. Write a Java program to implement echo command in client server socket
programming.
11. Write a Java program to implement Trace-route command.
12. Write a Java program to implement Ping command.
13. Write a Java program to display the class of IP address, network mask and generate the
subnet IP address based on the subnet bits entered from the keyboard.
14. Write a Java program to implement sliding window protocol at the transport layer.
15. Write a Java program to transfer file using TCP?
SEMESTER-V
Credits
L T P C
CSE 306 Compiler Design C 3 0 0 3
UNIT I: INTRODUCTION TO COMPILERS

Translators-Compilation and Interpretation-Language processors -The Phases of Compiler-Errors
Encountered in Different Phases-The Grouping of Phases-Compiler Construction Tools -
Programming Language basics.
UNIT II: LEXICAL ANALYSIS

Need and Role of Lexical Analyzer-Lexical Errors-Expressing Tokens by Regular Expressions-
Converting Regular Expression to DFA- Minimization of DFA-Language for Specifying Lexical
Analyzers-LEX-Design of Lexical Analyzer for a sample Language.
UNIT III: SYNTAX ANALYSIS

Need and Role of the Parser-Context Free Grammars -Top-Down Parsing -General Strategies-
Recursive Descent Parser Predictive Parser-LL (1) Parser-Shift Reduce Parser-LR (0) Item-
Construction of SLR Parsing Table -Introduction to LALR Parser - Error Handling and Recovery in
Syntax Analyzer-YACC-Design of a syntax Analyzer for a Sample Language.
UNIT IV: SYNTAX DIRECTED TRANSLATION & RUN TIME ENVIRONMENT

Syntax directed Definitions-Construction of Syntax Tree-Bottom-up Evaluation of S-Attribute
Definitions- Design of predictive translator - Type Systems-Specification of a simple type of checker-
Equivalence of Type Expressions-Type Conversions. Intermediate code generation: Quadruples,
Triples, Indirect triples, 3-address code RUN-TIME ENVIRONMENT: Source Language Issues-
Storage Organization-Storage Allocation- Parameter Passing-Symbol Tables-Dynamic Storage
Allocation-Storage Allocation in FORTAN.
UNIT V: CODE OPTIMIZATION AND CODE GENERATION

Principal Sources of Optimization-DAG- Optimization of Basic Blocks-Global Data Flow Analysis-
Efficient Data Flow Algorithms-Issues in Design of a Code Generator - A Simple Code Generator
Algorithm.
TEXTBOOKS
1. Compilers – Principles, Techniques and Tools, Alfred V Aho, Monica S. Lam, Ravi Sethi and
Jeffrey D Ullman, 2nd Edition, Pearson Education, 2007.
REFERENCES
1. Vassiliadis, Vassilis, et al. "D2. 3: Advanced compiler implementation." Center for Research
and Technology Hellas, Tech. Rep 2016.
2. Cooper, Keith, and Linda Torczon. Engineering a compiler. Elsevier, 2011.
3. Charles N. Fischer, Richard. J. LeBlanc, “Crafting a Compiler with C”, Pearson Education,
2008.
WEB RESOURCES
1. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-004-computation-
structures-spring-2017/c11/
2. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-035-computer-
language-engineering-spring-2010/
3. https://web.stanford.edu/class/archive/cs/cs143/cs143.1128/
SEMESTER-V
Credits
L T P C
CSE 306 L Compiler Design Lab C 0 0 2 1

Week 1: Language recognizer
1. Write a program in C that recognizes the following languages.
a. Set of all strings over binary alphabet containing even number of 0’s and even number
of 1’s.
b. Lab Assignment: Set of all strings ending with two symbols of same type.
Week 2: Implementation of Lexical analyzer using C
2. Implement lexical analyzer using C for recognizing the following tokens:
• A minimum of 10 keywords of your choice
• Identifiers with the regular expression : letter(letter | digit)*
• Integers with the regular expression: digit+
• Relational operators: <, >, <=, >=, ==, !=
• Storing identifiers in symbol table.
• Using files for input and output.
Week 3: Introduction to LEX tool
3. Implement the following programs using Lex tool
a. Identification of Vowels and Consonants
b. count number of vowels and consonants
c. Count the number of Lines in given input
d. Recognize strings ending with 00
e. Recognize a string with three consecutive 0’s
Week 4: Implementation of lexical analyzer using LEX
4. Implement lexical analyzer using LEX for recognizing the following tokens:
• A minimum of 10 keywords of your choice
• Identifiers with the regular expression : letter(letter | digit)*
• Integers with the regular expression: digit+
• Relational operators: <, >, <=, >=, ==, !=
• Ignores everything between multi line comments (/* …. */)
• Storing identifiers in symbol table
• Using files for input and output.
Week 5: Lexical Analyzer
5. Lab Assignment:
Consider the following mini Language, a simple procedural high-level language, only
operating on integer data, with a syntax looking vaguely like a simple C crossed with Pascal.
The syntax of the language is defined by the following BNF grammar:
<program> ::= <block>

<block> ::= { <variabledefinition> <slist> } | { <slist> }
<variabledefinition> ::= int<vardeflist>;
<vardeflist> ::= <vardec> | <vardec>, <vardeflist>
<vardec> ::= <identifier> | <identifier> [ <constant> ]
<slist> ::= <statement> | <statement>; <slist>
<statement> ::= <assignment> | <ifstatement> | <whilestatement> | <block> | <printstatement> |
<empty>
<assignment> ::= <identifier> = <expression> | <identifier> [ <expression> ] = <expression>
<ifstatement> ::= <bexpression> then <slist> else <slist> endif | if <bexpression> then <slist> endif
<whilestatement> ::= while <bexpression> do <slist> enddo
<printstatement> ::= print ( <expression> )
<expression> ::= <expression> <additionop> <term> | <term> | addingop> <term>
<bexpression> ::= <expression> <relop> <expression>
<relop> ::= < | <= | == | >= | > | !=
<addingop> ::= + | -
<term> ::= <term><mulitop> <factor> | <factor>
<multop> ::= * | /
<factor> ::= <constant> | <identifier> | <identifier> [ <expression> ] | ( <expression> )
<constant> ::= <digit> | <digit> <constant>
<identifier> ::= <identifier> <letterordigit> | <letter>
<letterordigit> ::= <letter> | <digit>
<letter> ::= a|b|c|d|e|f|g|h|i|j|k|l|m|n|o|p|q|r|s|t|u|v|w|x|y|z
<digit> ::= 0|1|2|3|4|5|6|7|8|9
<empty> has the obvious meaning
Comments (zero or more characters enclosed between the standard C / Java style comment brackets
/*...*/) can be inserted. The language has rudimentary support for 1-dimensional arrays. The
declaration int a[3] declares an array of three elements, referenced as a[0], a[1] and a[2]. Note also that
you should worry about the scoping of Names.
A simple program written in this language is:

{ int a[3], t1, t2;
t1 = 2; a[0] = 1; a[1] = 2; a[t1] = 3;
t2 = -(a[2] + t1 * 6)/ a[2] -t1);
if t2 > 5 then
print(t2);
else {
int t3;
t3 = 99;
t2 = -25;
print(-t1 + t2 * t3); /* this is a comment on 2 lines */
} endif
}
Design a Lexical analyser for the above language. The lexical analyser should ignore redundant spaces,
tabs, and newlines. It should also ignore comments. Although the syntax specification states that
identifiers can be arbitrarily long, you may restrict the length to some reasonable value.
Week 6: Recursive Descent Parser

6. Implement Recursive Descent Parser for the Expression Grammar given below.
E → TE’
E’→ +TE’ | ͼ
T → FT’
T’→ *FT’ | ͼ
F → (E) | i
7. Lab Assignment: Construct Recursive Descent Parser for the grammar

G = ({S, L}, {(, ), a, ,}, {S → (L) | a ; L→ L, S | S}, S) and verify the acceptability of the
following strings:
i. (a,(a,a))
ii. (a,((a,a),(a,a)))
You can manually eliminate Left Recursion if any in the grammar.
Week 7: Predictive parser

8. Write a C program for the computation of FIRST and FOLLOW for a given CFG
Week 8: Predictive Parser

9. Implement non-recursive Predictive Parser for the grammar
S -> aBa
B -> bB | ε
A b $
S S→aBa
B B→ε B→bB
10. Lab Assignment: Implement Predictive Parser using C for the Expression Grammar
E → TE’
E’→ +TE’ | ε
T → FT’
T’→ *FT’ | ε
F → (E) | d
Week 9: Shift Reduce Parser
11. Implementation of Shift Reduce parser using C for the following grammar and illustrate the
parser’s actions for a valid and an invalid string.
E→E+E
E→E*E
E→(E)
E→d
12. Lab Assignment: Implementation of Shift Reduce parser using C for the following grammar
and illustrate the parser’s actions for a valid and an invalid string.
S –> 0S0 | 1S1 | 2
Week 10: LALR Parser
13. Implement LALR parser using LEX and YACC for the following Grammar:
E → E+T |T
E’→ T*F | F
F → (E) | d
14. Lab Assignment: Implement LALR parser using LEX and YACC for the following
Grammar by specifying proper precedence for operators:
E → E+E | E-E | E*E | E/E | -E | (E) | digit
Week 11:Intermediate code generation

15. Generate quadruples for given arithmetic expression using LEX and YACC.
Week 12: Intermediate code generation
16. Generate 3-address code for if statement using LEX and YACC.
17. Lab Assignment: Generate 3-address code for while statement using LEX and YACC.
Week 13: Code optimization
18. Implement constant propagation and folding using C for a given set of intermediate
instructions.
19. Lab Assignment: Write a program to eliminate dead code
Week 14: Code optimization
20. Write a program to eliminate common sub expressions
21. Lab Assignment: Write a program to perform loop unrolling
Week 15: Code Generation
22. Generate machine code from the abstract syntax tree generated by the parser. The following
instruction set may be considered as target code. The following is a simple register-based
machine, supporting a total of 17 instructions. It has three distinct internal storage areas. The
first is the set of 8 registers, used by the individual instructions as detailed below, the second
is an area used for the storage of variables and the third is an area used for the storage of
program. The instructions can be preceded by a label. This consists of an integer in the range
1 to 9999 and the label is followed by a colon to separate it from the rest of the instruction. The
numerical label can be used as the argument to a jump instruction, as detailed below. In the
description of the individual instructions below, instruction argument types are specified as
follows:
R specifies a register in the form R0, R1, R2, R3, R4, R5, R6 or R7 (or r0, r1, etc.).
L Specifies a numerical label (in the range 1 to 9999).
V Specifies a “variable location” (a variable number, or a variable location pointed to by
a register -see below).
A Specifies a constant value, a variable location, a register, or a variable location pointed
to by a register (an indirect address). Constant values are specified as an integer value,
optionally preceded by a minus sign, preceded by a #symbol. An indirect address is
specified by an @followed by a register. So, for example, an A-type argument could
have the form 4 (variable number 4), #4 (the constant value 4), r4 (register 4) or @r4
(the contents of register 4 identifies the variable location to be accessed).
The instruction set is defined as follows:
LOAD A,R
loads the integer value specified by A into register R.
STORE R,V
stores the value in register R to variable V.
OUT R
outputs the value in register R.
NEG R
negates the value in register R.
ADD A,R
adds the value specified by A to register R, leaving the result in register R.
SUB A,R
subtracts the value specified by A from register R, leaving the result in register R.
MUL A,R
multiplies the value specified by Aby register R, leaving the result in register R.
DIV A,R
divides register R by the value specified by A, leaving the result in register R.
JMP L
causes an unconditional jump to the instruction with the label L.
JEQ R,L
jumps to the instruction with the label L if the value in register R is zero.
JNE R,L
jumps to the instruction with the label L if the value in register R is not zero.
JGE R,L
jumps to the instruction with the label L if the value in register R is greater than or equal
to zero.
JGT R,L
jumps to the instruction with the label L if the value in register R is greater than zero.
JLE R,L
jumps to the instruction with the label L if the value in register R is less than or equal
to zero.
JLT R,L
jumps to the instruction with the label L if the value in register R is less than zero.
NOP
is an instruction with no effect. It can be tagged by a label.
STOP
stops execution of the machine. All programs should terminate by executing a STOP
instruction
SEMESTER-V
Credits
L T P C
CSE 304 Database Management System C 3 0 0 3
UNIT I: IINTRODUCTION TO DBMS AND RELATIONAL MODEL

File Processing System, Advantages of DBMS over File Processing System, Database System
Applications DBMS Architecture: The three-schema architecture, Data Independence: Logical and
Physical Data Models: Hierarchical, network and relation models, Introduction to relational model,
concepts of domain, attribute, tuple, relation, importance of null values. Database constraints (Domain,
Key constraints, integrity constraints) and their importance.
UNIT II: QUERY PROCESSING

Relational Algebra, Relational Calculus, Introduction to SQL: Database Objects- DDL Schema
definitions. DML- Insert, select, update, delete. Views, exercise on SQL queries. Transaction support
in SQL: Aggregate Functions, Null Values, Views, Complex Integrity Constraints in SQL, Assertions,
Triggers.
UNIT III: CONCEPTUAL MODEL AND DATABASE DESIGN

Entity Relationship model Entity types, Entity Sets, Attributes, and Keys Relationships, Relationship
types and constraints, Weak Entity types. Enhanced ER (EER) Modeling: Super/Sub Classes
Specialization and Generalization. Constraints and characteristics of Specialization and
Generalization. Example EER Schema. Basics of Normalization, Normal Forms: First Normal Form
(1NF), Second Normal Form (2NF), Third Normal Form (3NF), BCNF, 4NF.
UNITIV: TRANSACTION PROCESSING, CONCURRENCY CONTROL AND RECOVERY

Introduction of transaction processing, advantages, and disadvantages of transaction processing
system, Serializability and Recoverability of transaction, Concurrency Control, Lock based Protocols,
Timestamp Based Protocols – Validation based Protocols - Multiple Granularity Locking, Recovery
techniques.
UNIT V: OVERVIEW OF STORAGE AND INDEXING

Data on External Storage, File Organization, and Indexing - Clustered Indexes, Primary and Secondary
Indexes.
Indexed Sequential Access Methods (ISAM) B+ Trees: Tree Structure, Search, Insert, Delete. Hash
Based Indexing: Static Hashing, Extendable hashing, Linear Hashing, Extendible vs. Linear Hashing.
TEXTBOOKS
1. Ramez Elmasri and Shamkant Navathe. 2010. Fundamentals of Database Systems (6th ed.).
Addison-Wesley Publishing Company, , USA.
REFERENCES
1. R. Ramakrishnan, J. Gehrke, Database Management Systems, McGraw Hill, 2004.
2. A. Silberschatz, H. Korth, S. Sudarshan, Database system concepts, 5/e, McGraw Hill, 2008.
3. Database system Implementation: Hector Garcia-Molina Jeffrey D. Ullman Jennifer Widom,
Prentice Hall, 2000.
4. C.J. Date. 2003. An Introduction to Database Systems (8 ed.). Addison-Wesley Longman
Publishing Co., Inc., Boston, MA, USA.
SEMESTER-V
Credits
L T P C
CSE 304 L Database Management System Lab C 0 0 2 1

Exercise-I
Create a data file to store records of the students (fields: rollno, Name, branch,age). (ii) Sort the
records of the file based on the rollno of the students. (iii) Perform external sorting procedure (based
on the roll number) on two data files which store records of the students and store the result in to the
third data file.
Exercise-II
Store student records (fields: rollno,Name,branch,age) in a data file and perform linear search in the
data file by reading rollno as input and then display the student details and display the time required
to do this operation.
Exercise-III
Store student records (fields: rollno,Name,branch,age) in a data file and build an index file by
considering the rollno as the key.
i.Perform linear search in the index file by reading rollno as input and then display the student
details by reading from the data file and display the time required to do this operation.
ii.Perform binary search in the index file (by sorting the index file based on the rollno) by
reading rollno as input and then display the student details by reading from the data file and
display the time required to do this operation.
Exercise-IV
Store student records (fields: rollno,Name,branch,age) in a data file and build an index file by using
binary search tree ( rollno is used as the key).
i.Perform search in the index file by reading rollno as input and then display the student details
by reading from the data file and display the time required to do this operation.
ii.Add and delete the student records from the data file and then perform corresponding
modifications in the index file.
Exercise-V
hash table (rollno is used as the key here).
iii.Perform search in the index file by reading rollno as input and then display the student details
by reading from the data file and display the time required to do this operation.
i.Add and delete the student records from the data file and then perform corresponding
modifications in the index file.
Exercise-VI
Consider the following relations.
Suppliers (sid: integer, sName: string, address: string)
Parts (pid: integer, pName: string, color: string)
Catalog ( sid: integer, pid: integer, cost: real)
The key fields are underlined, and the domain of each field is listed after the field Name.
Therefore, sid is the key for Suppliers, pid is the key for Parts, and sid and pid together form
the key for Catalog. The Catalog relation lists the prices charged for parts supplied by Suppliers.
Write SQL statements for the following.

a. Find the Names of suppliers who supply some red color part.
b. Find the sids of suppliers who supply some red color part and having office located at
‘Chennai’
c. Find the average cost of red color parts supplied by various suppliers.
d. Find the Names of the supplier who is supplying most number of parts.
e. Find the sids of suppliers who supply every part.
f. Find the sids of suppliers who supply every red color part.
g. List the number of suppliers for each color of part.
h. Find the supplier who supplies the red color part at a cheaper rate.
i. For each color part, display the details of the suppliers who supply that part at a cheaper rate.
j. Display the Names of the suppliers along with the number of parts supplied by them.
k. Find the details of the supplier who supplies the costliest part.
l. Display the Names of the suppliers who are selling at least two parts.
Exercise-VII
A) Consider the COMPANY database schema shown in the figure.
i.Create a view that has department Name, manager Name and manager salary for every
department.
ii.Create a view that has project Name, controlling depart Name, number of employees, and total
hours worked per week on the project for each project with more than one employee working
on it.
iii.Create an updateable view for the relation DEPARTMENT
B) Create a materialized view for finding average salary of employees, average salary of managers,
average salary for each department and department(s) which spend more money on salary for the
employees.
C) Assume that Dno of EMPLOYEE relation has got NOT NULL constraint. Write a transaction
which inserts tuples in to the relations EMPLOYEE and DEPARTMENT without affecting integrity
constraints specified in the schema.
Exercise-VIII
A) Consider the following relations:
instructor(ID, Name, dept_Name, salary)
section(course_id, sec_ id, semester, year, building, room_ number, time_slot_id)
teaches(ID, course_id, sec_id, semester, year)
Write assertions for the following:
i.An instructor cannot teach in two different classrooms in a semester in the same slot
ii.An instructor cannot teach more than one course for the same semester
B) Consider the following relations.
product(maker, model, type)
pc(model, speed, ram, hd, price )
laptop(model, speed, ram, hd, screen , price )
printer(model, color, type, price )
Write triggers for the following:

(a) When updating the price of a PC, check that there is no lower priced PC with the same
speed.
(b) When inserting a new printer, check that the model number exists in product.
(c) When making any modification to the Laptop relation, check that the average price of
laptops for each manufacturer is at least Rs 1500.
C) Consider the following relations.
Emp (eno,eName,eage, salary,departno,supereno), dep(depno,depName,depage,eno),
depart(departno,departName,location)
Write stored procedures
i.to find the average salary of employees who have got more than two dependents
ii.to find the Names of employees (age is greater than 50) and their dependents (average age is
less than 10).
Exercise-IX
Write java programs (using JDBC)
a. to create the following relations emp (eno,eName,eage, salary,departno,supereno),
dep(depno,depName,depage,eno), depart(departno,departName,location) and insert at least
20 tuples for each relation.
b. (i) to find average age of employee’s department wise (ii) to list
department(s) (location wise) which pay less salary to the employees.
Exercise-X
B+ tree (rollno is used as the key here).
a. Perform search in the index file by reading roll no as input and then display the
student details by reading from the data file and display the time required to do this
operation.
b. Add and delete the student records from the data file and then perform corresponding
modifications in the index file
SEMESTER-V
Credits
L T P C
CSE 332 Industry Standard Coding Practice -IV ES 0 0 4 1
UNIT-I
Greedy Strategy, Problem solving on greedy problems: Fractional Selection of inputs, fractional
Knapsack, Sequencing problem solutions, Activity selection, Huffman Decoding, Scenario based
problem solving implementing Greedy Methods, Examples, Practice problems.
UNIT-II
Problem solving implementing Dynamic programming, Coding solutions to form Sub structures,
Problem solving on Dynamic Knapsack, Trip optimization problem, Finding the sub set sum,
Scenario based problem solving using Dynamic Programming approaches, Coding solutions on
Coin-change sub structure, Problem solving using Grid Memo, Problem solving on Longest
Common Sub string, Longest Common subsequence, Minimum Edit Distance problems, Examples,
Practice problems.
UNIT-III
Introduction to Graphs Problems, Types of graphs, Problem solving on graph traversals, Checking
the degree sequence, DFS, BFS, Scenario based problem solving implementing graphs, Introduction
to Graph Coloring, Introduction to DAG, Graph Check, DFS Spanning Tree, Strongly Connected
point, Graph Reduction, Topological Sorting Examples, Practice problems.
UNIT-IV
Introduction to Backtracking, Differences between backtracking and brute force methods, State
space diagram, N Queens problem, Finding the path & Grid based problems, iterative/loop free
approaches, Graph coloring, examples Finding a way, Solving Grid based backtracking problems,
Problem Solving with String Matching Patterns, KMP Algorithm, Trie data structure, Examples,
Practice problems.
UNIT-V
Problem solving Methods and techniques: Complete, precise and consistent specification of the
problem abstract, verification and analysis of the algorithm, Actions on the GitHub, Security
standards of the access, creating branches, Branching and merging, Examples, Practice problems.
SEMESTER-V
Credits
L T P C
ISES 301 Industry Specific Employability Skills-V HS 1 1 0 0
UNIT I: QUANTS
Advanced Algebra, Advanced P & C and Probability, Advanced Time, Speed and Distance, Advanced
Time and Work, Advanced Geometry and Mensuration.
UNIT II: COMMUNICATION SKILLS

Group discussion, Tell about yourself, Extempore, Mock interview, Video interview & Presentations
UNIT III: REASONING

Puzzle and Reasoning
Perspective.
Students.
SEMESTER - VI
SEMESTER-VI
Credits
L T P C
CSE 305 Software Engineering C 3 0 2 4
UNIT I: SOFTWARE PROCESS AND AGILE DEVELOPMENT

Introduction to Software Engineering, Software Process, Perspective and Specialized Process Models
–Introduction to Agility-Agile Process-Extreme programming-XP Process.
UNIT II: REQUIREMENTS ANALYSIS AND SPECIFICATION

Software Requirements: Functional and Non-Functional, User requirements, System requirements,
Software Requirements Document – Requirement Engineering Process: Feasibility Studies,
Requirement’s elicitation and analysis, requirements validation, requirements management-Classical
analysis: Structured system Analysis, Petri Nets-Data Dictionary.
UNIT III: SOFTWARE DESIGN

Design process – Design Concepts-Design Model– Design Heuristic – Architectural Design -
Architectural styles, Architectural Design, Architectural Mapping using Data Flow- User Interface
Design: Interface analysis, Interface Design –Component level Design: Designing Class based
components, traditional Components.
UNIT IV: TESTING AND MAINTENANCE

Software testing fundamentals-Internal and external views of Testing-white box testing - basis path
testing-control structure testing-black box testing- Regression Testing – Unit Testing – Integration
Testing – Validation Testing – System Testing And Debugging –Software Implementation
Techniques: Coding practices-Refactoring-Maintenance and Reengineering-BPR model-
Reengineering process model-Reverse and Forward Engineering.
UNIT V: PROJECT MANAGEMENT

Software Project Management: Estimation – LOC, FP Based Estimation, Make/Buy Decision
COCOMO I & II Model – Project Scheduling – Scheduling, Earned Value Analysis Planning – Project
Plan, Planning Process, RFP Risk Management – Identification, Projection - Risk Management-Risk
Identification-RMMM Plan-CASE TOOLS.
TEXTBOOKS
1. Roger S. Pressman, Software Engineering – A Practitioner‟s Approach, Ninth Edition, Mc
Graw-Hill International Edition, 2020.
2. Ian Sommerville, Software Engineering, Tenth Edition, Pearson Education Asia, 2015.
REFERENCES
1. Rajib Mall, Fundamentals of Software Engineering, Fifth Edition, PHI Learning Private
Limited, 2018.
2. Pankaj Jalote, Software Engineering, A Precise Approach, Wiley India, 2010.
3. Kelkar S.A., Software Engineering, Third Edition, Prentice Hall of India Pvt Ltd, 2013.
4. Stephen R. Schach, Object-oriented Software Engineering, Tata McGraw-Hill Publishing
Company Limited,2008.
WEB RESOURCES
1. https://ocw.mit.edu/courses/aeronautics-and-astronautics/16-355j-software-engineering-
concepts-fall-2005/lecture-notes/
SEMESTER-VI
Credits
L T P C
CSE305 L Software Engineering Lab C 0 0 2 1

Week 1: Software Requirement Specification
1. Develop requirements specification for a given problem
Week 2: Data Flow Diagram (DFD)
2. Develop DFD Model (Level 0, Level 1 DFD and data dictionary) of the sample problem
Week 3: DFD and Structured chart
3. To perform the function-oriented diagram: DFD and Structured chart
Week 4: Use case Diagram
4. To perform the user’s view analysis: Use case diagram
Week 5: Class Diagram
5. To draw the structural view diagram: Class diagram
Week 6: Object Diagram
6. To draw the structural view diagram: Class diagram, object diagram
Week 7: Package Diagram
7. To draw the structural view diagram: Package Diagram
Week 8: Sequence Diagram
8. To draw the structural view diagram: Sequence Diagram
Week 9: Interaction Overview Diagram
9. To draw the structural view diagram: Interaction Overview Diagram
Week 10: State-chart Diagram
10. To draw the behavioral view diagram: State-chart diagram
Week 11: Activity diagram
11. To draw the behavioral view diagram: Activity diagram
Week 12: Component diagram
12. To draw the implementation view diagram: Component diagram
Week 13: Deployment diagram
13. To draw the environmental view diagram: Deployment diagram
Week 14: Unit Testing
14. To perform various testing using the testing tool -unit testing
Week 15: Integration Testing
15. To perform various testing using the testing tool -integration testing
TEXTBOOKS
1. Roger S. Pressman, Software Engineering – A Practitioner‟s Approach, Ninth Edition, Mc
Graw-Hill International Edition, 2020.
2. Ian Sommerville, Software Engineering, Tenth Edition, Pearson Education Asia, 2015.
3. Rajib Mall, Fundamentals of Software Engineering, Fifth Edition, PHI Learning Private
Limited, 2018.
4. Pankaj Jalote, Software Engineering, A Precise Approach, Wiley India, 2010.
5. Kelkar S.A., Software Engineering, Third Edition, Prentice Hall of India Pvt Ltd, 2013.
6. Stephen R. Schach, Object-oriented Software Engineering, Tata McGraw-Hill Publishing
Company Limited,2008
7. https://ocw.mit.edu/courses/aeronautics-and-astronautics/16-355j-software-engineering-
concepts-fall-2005/lecture-notes/
9. Grady Booch, James Rumbaugh, Ivar Jacobson, Unified Modeling Language User Guide,
The, 2nd Edition, 2016.
10. Dr.K.V.N.S. Prasad, “Software Testing Tools”, 1st Edition, Dream tech, 2011.
SEMESTER VI
Credits
L T P C
CSE 340 UROP PR 0 0 6 3
Department of Computer Science and Engineering, UROP Guidelines
1. Tentative date of commencement of Research Project is along with 6th semester each year.
2. The duration of the Project is 12 weeks or end by the 6th semester.
3. Maximum of 5 students form a team
4. Each faculty co-ordinates maximum 5teams
5. The title of the research work, scope, methodology and expected outcomes need to be approved
by the Faculty mentor/guide.
6. Grading has to be completed by the concerned faculty by the end of 6th semester.
7. Number pf Credits for CSE340 is 3.
General Guidelines for UROP project report and Research work.
These guidelines explain briefly the mechanics of writing a research paper in Computer Science and
Engineering. These guidelines are generic and can be customized to fit most of the research works
The writing can start with the abstract, which can be approximately one page 10–20 sentences. The
abstract will be refined and updated as a continuous process. The abstract can concisely (1) identify
the research topic, (2) identify the benefits and advantages that result (3) and if there is novelty,
describe the novelty of the presented work.
Section 1: Introduction (Motivation)
Although the title of the starting section is “Introduction” it should really be Motivation. In one or two
paragraphs, the topic has to be introduced. This is followed with useful of the work, including possible
applications of the work. Possible points to mention include:
1. Does the research work describe the state-of-the-art in that research domain?
2. What is the relevance of this work in filling any research gap?
3. Who will potentially benefit from the work?
4. Does the presented work provide a new technique of some sort?
5. Does this research work provide any new insight in some way?
6. Is it a review work which gives an insight to the current research in a particular domain?
Words like, contribute, benefit, advantageous, and possibly novel are used in this list. The presented
work often builds on a previous system or algorithm. If so, your work may inherit benefits from the
previous work. Those inherited advantages may also be listed.The introduction section then concludes
with how the rest of the research paper is organized.
Section 2: Related Works: Presents review of the previous work on this topic.
The related work section demonstrates to the reader that you have done your homework (research),
reviewed the previous literature, and now are ready to present your contribution based what has been
previously published. The review is confined to relevant and recent research works in the domain of
the proposed research. One of the difficult aspects of the related work section is choosing the proper
scope. There is some subjectivity in choosing which books or papers to refer to and also importantly,
which previous literature not to refer to. This is something an advisor is able to help with.
Section 3: Presents the proposed work/experimental/simulation specifications.
Section 4: Presents any algorithms or procedures used.
Next section: Can represent an evaluation of the results and the
Last section: May present conclusions and future work.
Citations
Any figure, image, or equation that is taken from another source must be cited. Content and
terminology from other sources must also be cited. For more information about citations and their use,
see:
http://www.plagiarism.org/. Click on the “How to cite sources” link.
References should be accurate and complete, i.e., with page numbers etc. A paper without complete
and correct references can leave a bad impression on the reader and detract from a paper’s credibility.
Mark Distribution: (As per the Original Plan. May be reviewed)
1. Internal evaluation by Guide: 50 marks

2. External evaluation by a Committee: 50 marks
(Project Report, Demonstration and Presentation)
SEMESTER-VI
Credits
L T P C
ISES 302 Industry Specific Employability Skills-VI HS 1 1 0 0
UNIT I: QUANTS
Advanced LR & DJ
UNIT II: COMMUNICATION SKILLS

Group discussion, Tell about yourself, Extempore, Mock interview, Video interview & Presentations
UNIT III: REASONING

Puzzle and Reasoning
Perspective.
Students.
SEMESTER – VII & VIII
SEMESTER VII /VIII
Credits
L T P C
Semester VII
CSE 460 Capstone Project Phase I PR 0 0 12 6
Semester VIII
CSE 461 Capstone Project Phase II PR 0 0 12 6
Capstone Project Guidelines

Introduction
These guidelines are conceived as a set of procedures stating broad expectations from both students
and mentors of the Capstone project which is part of the B.Tech CSE curriculum. These guidelines are
intended to make the project work evaluation process easier, formal and more authentic. The Capstone
Project spans 2 semesters which are the 7th and 8th semesters. The total number of Credits offered for
the capstone project is 12. The total credit is split into 6+6 for 7th and 8th semesters respectively. The
Capstone project has to be sufficiently complex and feasible so as to be considered for 12 Credits. The
evaluation of the project is done by a review panel comprising department faculty members and the
review process is continuous. In the first review by the constituted panel, the project may be accepted
or rejected or major/minor changes can be suggested.
Project Selection
Capstone project may be an in-campus project or can be mapped with internship carried out in the
industry or the research internship carried out in the other premier Universities in India/Abroad.
In campus project: The idea for student's Project may be a proposal from a faculty member or
student's own, or perhaps a combination of the two. The project has to be sufficiently complex and
feasible. Students are advised to choose a project that involves a combination of sound background
research, a solid implementation, or piece of theoretical work, and a thorough evaluation of the
Project’s output. Interdisciplinary Project proposals and innovative Projects are encouraged and more
appreciable.
Mapping with any Internship:

a. Any type of internships can be carried out by the students in the 7th and 8th semester after getting
the due approval from the Project coordinator and the Head of the department.
b. The internship period has to be a minimum of 10 weeks of duration in each semester and the
students could have carried out the practical work for at least 180 hrs during this period.
c. The internship has to involve some Software/Hardware design and implementation component
and/or research component and the complexity of this work is expected to match the
requirements of Capstone Project work.
Mentor allocation process: Students can form a batch of 4 (5 may be allowed in exceptional cases on
the discretion of the project coordinators) and select their mentor provided the Faculty member accepts
them and the faculty member has less than the specified number projects under his/her mentorship.
Project Equipment: In case of deserving projects for limited financing of equipment, the students can
approach the concerned university authorities following due procedure.
Meetings with Your Supervisor:
Instructions to students: You must make sure that you arrange regular meetings with your Mentor. The
meetings may be brief once your project is under way, but your Mentor needs to know that your work
is progressing. You are also expected to be contactable throughout the project. You should inform the
Mentor your contact details and keep these updated if these change.
Instructions to Mentors: Mentors are advised to maintain a project dairy depicting attendance of
student and progress of project.
Legal and Ethical Considerations: If a student want to do some project with some company where
their relatives or friends work, the details need to be disclosed to their mentor. The mentor has to report
the same to the project coordinators for permission. Again, if a student doing internship with a
company, the data, procedures/algorithms and softwaredeveloped may be classified and may not be
allowed to submit in the report. The students need to consider that before requesting mapping.
Project Report format: Format of the report is similar to the format of standard Journal papers
published. (Abstract-Literature survey-Methodology-Algorithms-Simulation-Results-explanation of
results-Future work etc)
Project milestones and Assessment

Starting date of the project to be taken as the commencement date of 7th semester. A student is
expected to finish first two stages in 7th semester and remaining in 8th. The students are expected to
plan from the beginning for at least one research publication in a reputed journal.
7th Semester:
Stage 1: Title, Scope of the project and Literature survey to be submitted within 4 weeks from the
commencement of the project. In the first review by the constituted panel, the project may be accepted
or rejected or major/minor changes can be suggested.
Stage 2: Methodology, Requirement analysis and Deliverables to be submitted within 8 weeks from
the commencement of the project.
Stage 3: Algorithms, project design and implementation plan have to be submitted within 12 weeks of
the commencement of the 8th semester. Internal review will be conducted by the Mentor and this
review has a weightage of 50%.
8th Semester:
Stage 4: Project implementation to be done and demonstrate that the project meets the requirements
and expectations.
Stage 5: The results need to be analyzed and if any fine tuning required is to be done.
Final evaluation for 7th and 8th semesters: by expert committee at the end of the 14th week
and this evaluation has a weightage of 50%.
SPECIALIZATION STREAMS
Artificial Intelligence and Machine Learning Stream
Credits
L T P C
CSE 413 Artificial Intelligence SE 3 0 0 3
What is Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of
Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents.
UNIT II: SEARCH

Introduction to Search, Searching for solutions, Uniformed search strategies, Informed search
strategies, Local search algorithms and optimistic problems, Adversarial Search, current-best-
hypothesis search, least commitment search.
UNIT III: KNOWLEDGE REPRESENTATION AND REASONING

Inference, Propositional Logic, Predicate Logic (first order logic), Logical Reasoning, Forward
&Backward Chaining, Resolution; AI languages and tools - Lisp, Prolog, CLIPS.
UNIT IV: PROBLEM SOLVING

Formulating problems, problem types, Solving Problems by Searching, heuristic search techniques,
constraint satisfaction problems, stochastic search methods.
UNIT V: LEARNING
Overview of different forms of learning, decision trees, rule-based learning, neural networks,
reinforcement learning.
Game playing: Perfect decision game, imperfect decision game, evaluation function, minimax, alpha-
beta pruning.
TEXTBOOKS
1. Stuart Russell, Peter Norvig, “Artificial Intelligence – A Modern Approach”,
Pearson Education, Third Edition, Pearson Education, 2008.
REFERENCES
1. Elaine Rich and Kevin Knight, “Artificial Intelligence”, McGraw-Hill, 3 edition, 2017.
rd
2. E Charniak and D McDermott, “Introduction to Artificial Intelligence”, Pearson.

Credits
L T P C
CSE 413 L Artificial Intelligence Lab SE 0 0 2 1

1. Week 1: Artificial Intelligence Problem identification and PEAS description.
2. Week 2: Introduction to AI programming Language PROLOG.
3. Week 3: Study of facts, objects, predicates and variables in PROLOG.
4. Week 4: Study of arithmetic operators, simple input/output and compound goals in PROLOG.
5. Week 5: Study of string operations in PROLOG. Implement string operations like substring,
6. string position, palindrome etc.
7. Week 6: Write a prolog program to implement all set operations (Union, intersection,
8. complement etc.
9. Week 7: Write a program for Usage of rules in Prolog.
Create a family tree program to include following rules 1. M is the mother of P if she is a parent
of P and is female 2. F is the father of P if he is a parent of P and is male 3. X is a sibling of Y
if they both have the same parent. 4. Then add rules for grandparents, uncle-aunt, sister and
brother. Based on the facts, define goals to answer questions related to
10. Week 8: Write programs for studying Usage of arithmetic operators in Prolog.
Accept Name of the student, roll no, his/her subject Name, maximum marks and obtained
marks in the subject. (Take marks of at least 6 subjects). Compute the percentage of a student.
Display his result with other information.
Accept department, designation, Name, age, basic salary, house rent allowance (HRA) of an
employee. Compute dearness allowance (DA) which is 15% of basic salary. Determine the
gross salary (basic salary+HRA+DA) of the employee. Display all information of the employee
(Generate Payslip).
11. Week 9: Implement a program for recursion and list in PROLOG.
12. Week 10: WAP for studying usage of compound object and list in Prolog.
Write a program to maintain inventory items using a compound object:
(i) Accept from user the details of at least 10 objects. (ii)Display from user the details of objects
entered by user (2) Find and display odd and even numbers from a given input list.
13. Week 11: Write a prolog program to solve “Water Jug Problem”.
14. Week 12: Write a program to implement a monkey banana problem.
15. Week 13: Write a program to implement 8 Queens Problem.
16. Week 14: Write a program to solve traveling salesman problem.
17. Week 15: Write a program to solve water jug problem using LISP.
Credits
L T P C
CSE 336 Machine Learning SE 3 0 0 3
UNIT I
Introduction: Introduction to Machine Learning: Introduction. Different types of learning, Hypothesis
space and inductive bias, Evaluation. Training and test sets, cross validation, Concept of over fitting,
under fitting, Bias and Variance
Linear Regression: Introduction, Linear regression, Simple and Multiple Linear regression,
Polynomial regression, evaluating regression fit.
UNIT II
Decision tree learning: Introduction, Decision tree representation, appropriate problems for decision
tree learning, the basic decision tree algorithm, hypothesis space search in decision tree learning,
inductive bias in decision tree learning, issues in decision tree learning, over fitting in decision tree
and methods to avoid over fitting.
Instance based Learning: K nearest neighbour, theCurse of Dimensionality, Feature Selection:

univariate , multivariate feature selection approach, missing values ratio, high correlation filter, low
variance filter, feature selection using decision tree, Feature reduction Techniques: Principal
Component Analysis, Linear Discriminate Analysis
Recommender System: Content based system, Collaborative filtering based
UNIT III
Probability and Bayes Learning: Bayesian Learning, Naïve Bayes, Python exercise on Naïve Bayes,
Logistic Regression
Support Vector Machine: Introduction, the Dual formulation, Maximum margin with noise, nonlinear
SVM and Kernel function, solution to dual problem
UNIT IV
Artificial Neural Networks: Introduction, Biological motivation, ANN representation, appropriate
problem for ANN learning, Perceptron, multilayer networks and the back propagation algorithm
UNIT V
Ensembles: Introduction, Bagging and boosting, Random forest, Discussion on some research papers.
Clustering: Introduction, K-mean clustering, agglomerative hierarchical clustering, Python exercise on

k-mean clustering.
TEXTBOOKS
1. Machine Learning. Tom Mitchell. First Edition, McGraw- Hill, 1997.
2. Alpaydin, Ethem. Introduction to machine learning. MIT press, 2020.
REFERENCES
1. Kevin P. Murphy, “Machine Learning: A Probabilistic Perspective”, MIT Press, 2012.
2. Christopher Bishop, “Pattern Recognition and Machine Learning” Springer, 2007.

Credits
L T P C
CSE 336 L Machine Learning Lab SE 0 0 2 1

1. Basic exercises on Python Machine Learning Packages such as Numpy, Pandas and matplotlib
2. Python exercise on Feature engineering, data visualisation
3. Programs on Covariance, Correlation, Covariance Matrix and Correlation Matrix
4. Implement Linear Regression and calculate sum of residual error
5. Program to implement different distance functions
6. Program to implement decision tree learning
7. Program to implement K nearest neighbour classifier
8. Program to implement Principle Component Analysis
9. Program to implement perceptron for different learning task
10. Programs to implement ADALINE and MADALINE for given learning task
11. Program to implement classification task using Support Vector machine
12. Programs to implement different Clustering algorithms
REFERENCE BOOKS
1. Swamynathan, Manohar. Mastering machine learning with python in six steps: A practical
implementation guide to predictive data analytics using python. Apress, 2019.
2. Raschka, Sebastian. Python machine learning. Packt publishing ltd, 2015.
Credits
L T P C
CSE 314 Digital Image Processing SE 3 0 0 3
UNIT I
Introduction: Digital Image fundamentals: Image sampling and quantization, relationship between
pixels, Image acquisition and Pre-processing: Intensity transformations and spatial filtering, some
basic intensity transformation functions, Histogram processing, spatial filters for smoothing and
sharpening.
UNIT II
Filtering in the Frequency Domain: basic filtering in the frequency domain, image smoothing and
sharpening Image Restoration: Image restoration/degradation model, noise models, restoration in the
presence of noise only, estimating the degradation function.
UNIT III
Image segmentation: Fundamentals, point, line detection, basic edge detection techniques, Hough
transform, Thresholding, basic global thresholding, optimal thresholding using Otsu’s method, multi-
spectral thresholding, Region based segmentation, region growing, region splitting and merging.
UNIT IV
Color Image Processing: color models, Color transformation Image Compression: Fundamentals,
Some basic compression methods Morphological Image Processing: Erosion and Dilation, opening
and closing, thinning, skeletonisation.
UNIT V
Image Representation: Shape features (Region-based representation and descriptors), area, Euler’s
number, eccentricity, elongatedness, rectangularity, direction, compactness, moments, covex hull,
texture features, color features. Object and Pattern Recognition: Pattern and pattern classes, Matching,
minimum distance or nearest neighbor classifier, matching by correlation, Optimum statistical
classifier, Neural network classifier.
TEXTBOOKS
1. R.C. Gonzalez, R.E. Woods, Digital Image Processing, 3rd Edition, Pearson Education
REFERENCES
1. S. Sridhar, Digital Image Processing, Oxford University Press, 2011.
2. Milan Sonka, Vaclav Hlavac and Roger Boyele, Image processing, analysis, and machine
vision. 3e, Cengage Learning, 2014.
3. Computer Vision A modern approach, David A. Forsyth and Jeam Ponce, Pearson Education.
Credits
L T P C
CSE 314 L Digital Image Processing Lab SE 0 0 2 1

1. Perform the following operations using library functions
a. Read, Display and write any color image in other formats.
b. Find RED, GREEN and BLUE plane of the color image.
c. Convert color image into gray scale image and binary image.
d. Resize the image by one half and one quarter.
e. Image rotates by 45, 90 and 180 degrees.
2. Create black and white images (A) of size 1024x1024. Which consists of alternative horizontal
lines of black and white? Each line is of size 128.
Create black and white images (B) of size 1024x1024. Which consists of alternative vertical
lines of black and white? Each line is of size128.Perform the following operations on Image A
and Image B.
a. Image addition of A and B
b. Subtraction of A and B
c. Multiplying Images of A and B
a. Create a grayscale image of size 256x1024. Intensity of image should vary sinusoidal.
b. Create a white image of size 256x256, with black box of size 58x58 at centre.
3. Develop programs for following intensity transformation operation on a gray scale image.
Collect any gray scale image from any source. Process that image using these operations.
a. Image negative
b. Log transformation and inverse log transform: s = c log (1+r),
c is a const, r ≥ 0. s is pixel intensity of output image, r is the
pixel intensity of input image. Study the effect of constant c
on the quality of output image.
c. Power law transformation: Study the effect of different values of Gamma used in this
transformation.
d. Contrast stretching
e. Gray level slicing
4. Develop programs for following spatial filtering operations on a gray scale image.
a. Averaging: Implement averaging filtering operations for different window sizes and
study their effect on the quality of output image. Write your observations on output
image quality.
b. Weighted averaging: Implement weighted averaging filtering operations for different
window sizes and study their effect on the quality of output image. Write your
observations on output image quality.
c. Median filtering: Implement weighted averaging filtering operations for different
window sizes and study their effect on the quality of output image. Write your observations
on output image quality.
d. Max filtering
e. Min filtering
5. Take a gray scale image and add salt and pepper noise. Write programs for following operations
and observe their outputs
a. Linear smoothing or Image averaging
b. Weighted averaging
c. Median filtering. Compare the output quality among Image averaging and median
filtering.
d. Max filtering
e. Min filtering
6. Write programs to perform following sharpening operations on a gray scale image
a. Laplacian filter
b. Filtering using composite mask
c. Unsharp masking
d. High boost filtering
e. Filtering using first order derivative operators such as sobel and prewitt mask.
7. Write a program to improve contrast of an image using histogram equalization. The prototype
of the function is as below:
histogram_equalisation(input_Image, no_of_bins);
The function should return the enhanced image. Consider two low contrast input
images. Study the nature of the output image quality in each case by varying the number
of bins.
8. Take a low contrast gray scale image (A) and a high contrast gray scale image (B). Write a
program to improve the contrast of A with the help of image B using histogram specification
or matching. The prototype of the function is as below:
Histogram_sp(input_Image, specified_Iage, no_of_bins);
The function should return the enhanced image.
9. Develop programs to implement frequency domain smoothing filters (Ideal, Butterworth and
Gaussian) and apply these filters on a gray scale image.
a. Compare/comment on the output of Ideal, Butterworth and Gaussian Low pass Filters
having the same radii (cutoff frequency) value.
b. Consider a suitable gray scale image and demonstrate the ringing effect on the output
of Ideal low pass frequency domain filter.
c. Compare the output of Butterworth low pass filters (order n=2) for different cut-off
frequencies (5, 15, 30, 90, 120).
d. Compare the output of Gaussian low pass filters for different cut-off frequencies (5,
15, 30, 90, and 120).
10. Develop programs to implement frequency domain sharpening/High pass filters (Ideal,
Butterworth and Gaussian) and apply these filters on a gray scale image.
a. Compare/comment on the output of Ideal, Butterworth and Gaussian High pass Filters
having the same radii (cutoff frequency) value.
b. Consider a suitable gray scale image and demonstrate the ringing effect on the output
of Ideal high pass frequency domain filter.
c. Compare the output of Butterworth high pass filters (order n=2) for different cut-off
frequencies (5, 15, 30, 90, 120).
d. Compare the output of Gaussian high pass filters for different cut-off frequencies (5,
15, 30, 90, and 120).
11. Develop program to add different types of noise in a gray scale image and write functions to
implement following filters for image restoration in presence of these noises.
a. Remove Salt and Pepper Noise
b. Minimize Gaussian noise
c. Median filter and Weiner filter
12. Write and execute program for image morphological operations erosion and dilation.
13. Implement Morphological smoothing using opening and closing
14. Develop program to implement point and line detection masks. Detect points and lines using
these masks for a given gray scale image.
15. Develop programs for edge detection using different edge detection mask.
16. Develop programs to achieve image segmentation using
17. Basic Global thresholding
18. Optimal global thresholding or Otsu’s thresholding
19. Given a set of coordinates as boundary pixels in an image. Write a program to implement
Hough Transform for joining the points using different lines.
20. Given a MXN image. Write a program to find the Co-occurrence matrix for a given angle and
distance. Compute the Co-occurrence matrix features.
21. Given a MXN image. Write a program to find the Local Binary Pattern profile of the given
image.
Credits
L T P C
CSE 412 Principles of Soft Computing SE 3 0 0 3
UNIT I: INTRODUCTION TO SOFT COMPUTING, ARTIFICIAL NEURAL NETWORK

(ANN)
Fundamentals of ANN, Basic Models of an artificial Neuron, Neural Network Architecture, learning
methods, Terminologies of ANN, Hebb network, Supervised Learning Networks: Perceptron, Adaline,
Madaline, Multi-Layer Perceptron, Feed forward Back propagation Network: back propagation
learning, Learning Effect of Tuning parameters of the Back propagation.
UNIT II: RBF NETWORK, ASSOCIATIVE MEMORY

Auto, hetero and linear associative memory, network, Adaptive Resonance Theory: ART1, ART2,
Introduction to Computer vision, Introduction to Convolutional neural network, popular architectures:
Alex Net, Google Net, VGG Net.
UNIT III: FUZZY LOGIC

Fuzzy set theory: crisp sets, fuzzy sets, crisp relations, fuzzy relations, Fuzzy Systems: Crisp logic
predicate logic, fuzzy logic, fuzzy Rule based system, Defuzzification Methods, Fuzzy rule-based
reasoning.
UNIT IV: GENETIC ALGORITHMS

Fundamentals of genetic algorithms: Encoding, Fitness functions, Reproduction. Genetic Modeling:
Cross cover, Inversion and deletion, Mutation operator, Bit-wise operators, Bitwise operators used in
GA. Convergence of Genetic algorithm. Applications, Real life Problems Particle Swarm Optimization
and its variants.
UNIT V
Hybrid Soft Computing Techniques Hybrid system, neural Networks, fuzzy logic and Genetic
algorithms hybrids Genetic Algorithm based Back propagation Networks: GA based weight
determination applications: Fuzzy logic controlled genetic Algorithms soft computing tools,
Applications.
TEXTBOOKS
1. Principles of Soft Computing- S.N. Sivanandan and S.N. Deepa, Wiley India, 2nd Edition
2018.
REFERENCES:
1. Neuro Fuzzy and Soft Computing, J. S. R. JANG, C.T. Sun, E. Mitzutani, PHI.
2. Neural Networks, Fuzzy Logic, and Genetic Algorithm (synthesis and Application) S.
Rajasekaran, G.A. Vijayalakshmi Pai, PHI.
Credits
L T P C
CSE 412 L Principles of Soft Computing Lab SE 0 0 2 1

1. Write a Python Program to implement a perceptron. The input is your semester marks.
2. Write a python program to extend the exercise given above to implement Feed Forward
Network. The inbuilt function should not be used.
3. Write a python program to implement Hebb Network. The inbuilt function should not be used.
4. Write a python program to implement Multilayer Perceptron. The inbuilt function should not
be used.
5. Write a python program to implement any ANN with back propagation learning Algorithm.
6. Write a Python Program to implement ART1 and ART 2.
7. Write a python program to implement CNN.
8. Write a python Programming to realize the working principles of popular architectures such as
Alex Net, Google Net and VGG Net.
9. Write python Program to realize Fuzzy Sets arithmetic.
10. Write a python Program to realize fuzzy relations.
11. Write a python program to realize a fuzzy rule of any popular problem(s).
12. Write a python program to realize a defuzzification scheme for the above exercise.
13. Write a python Program to reason the fuzzy rules in exercises 12 and 13.
14. Write a python program to realize various steps of Genetic Algorithms.
15. Write a Python Program to realize GA based back propagation Networks.
16. Write a Python Program to realize Fuzzy Controlled Genetic Algorithms.
Cyber Security Stream
Credits
L T P C
CSES 337 Cryptography SE 3 0 0 3
UNIT I
History and overview of cryptography, Classical Encryption Techniques: Symmetric Cipher Model,
Substitution Techniques, Transposition Techniques, Rotor Machines, And Steganography
UNIT II
Stream Ciphers and Block Ciphers, Attacks on block ciphers, Block Cipher Principles, The Data
Encryption Standard (DES), Block Cipher Design Principles, Group, Rings, Field, Polynomial
Arithmetic, The Euclidean Algorithm, Finite Fields of the Form GF(2n)
UNIT III
Advanced Encryption Standard (AES), Stream Ciphers, RC4, The Chinese Remainder Theorem,
Public Key Cryptography and RSA Algorithm, Diffie-Hellman Key Exchange, Elliptic Curve
Cryptography.
UNIT IV
Cryptographic Hash Functions: Applications of Cryptographic Hash Functions, Two Simple Hash
Functions, Requirements and Security, Secure Hash Algorithm (SHA), SHA-3.
UNIT V
Introduction to Block Chain, Bitcoin basics, Smart Contracts, Blockchain development platforms and
APIs, Blockchain Ecosystems, Ethereum, Distributed Consensus, Blockchain Applications
1. Stallings, William. Cryptography and network security, Principle and Practice. Pearson
2. R. Stinson Cryptography, Theory and Practice (Fourth Edition Edition)
3. Handbook of Applied Cryptography by A. Menezes, P. Van Oorschot, S. Vanstone.
4. Melanie Swan, Blockchain, Blueprint for a new Economy, OReilly
Credits
L T P C
CSE 337 L Cryptography Lab SE 0 0 2 1

1. Write a program take text file as an input and print word, character count and ascii value of
each characters as output. (Hint: Use open(), read() and split()).
2. Write a encryption program: Input: computerscienceengineeringsrmuniversity Output:
gsqtyxivwgmirgiirkmriivmrkwvqyrmzivwmxc Hint: key =4 (play with ascii value).
3. Raju send an encrypted message (cipher text) “PHHW PH DIWHU WKH WRJD SDUWB” to
Rani. Can you build decryption process and find out what is the message (plain text) send to
Rani? Hint: try all keys.
4. Raju send encrypted message “ZICVTWQNGKZEIIGASXSTSLVVWLA” to Rani. Can you
build decryption process and find out what is the message send to Rani. Hint: try all keys for
each character.
5. Kohli have plain text “wewishtoreplaceplayer”. Can you build encryption process and find out
what is the cipher text he needs send to BCCI. Help him out by using monoalphabatic cipher.
Hint: use any one-to-one mapping between alphabets.
One to one
mapping
6. Kohli sent encrypted message (Cipher text) “SEEMSEAOMEDSAMHL” to Anushka. Can you
build decryption process and find out what is the message (plain text) send to Anushka. Hint:
use above one to one mapping between alphabets.
7. Raju want to build encrypted and decryption algorithms of Playfair Cipher. Help him to build
a key matrix using the key “srmapuniversity”
8. By using key matrix Raju want to send message “we are discovered save yourself” to Rani.
Can you build encryption process and find out what is the cipher text message send to Rani by
using palyfaircipher.
9. By using key “CBDE” Raju would like send message (plain text)“HELLO WORLD” to Rani.
Can you build encryption process and find out what is the encrypted message (cipher text) to
Raju by using Hill Cipher.Also Can you build decryption process and find out what is the decrypted
message (plain text) of cipher text "SLHZYATGZT" by using Hill Cipher.
10. Implementation of Encryption and Decryption of Vigenère Cipher
keyword deceptive
key: deceptivedeceptivedeceptive
plaintext: wearediscoveredsaveyourself
ciphertext: ZICVTWQNGRZGVTWAVZHCQYGLMGJ
11. Implement the Encryption and Decryption of Row Transposition.
Key: 4312567
Plaintext: a t t a c k p
ostpone
duntilt
woamxyz
Ciphertext: TTNAAPTMTSUOAODWCOIXKNLYPETZ
12. Implement the Euclidean Algorithm for integers and polynomials.
13. Implement AES Key Expansion.
14. Implementation of AES encryption and decryption
15. Implementation of Simplified DES Encryption and decryption
16. Implementation of RC4
17. Implementation of RSA algorithm
18. Implementation of Diffie-Helman key exchanges
19. Implementation of elliptic-curve cryptography
20. Implementation of Hash functions
Credits
L T P C
CSES 315 Network Security SE 3 0 0 3
UNIT I: NEED FOR SECURITY

Need for Security: Security Attack, Security Services, Information Security, Methods of
Protection.
Network Concepts: Basic Concepts of Computer Networks
Threats in Networks: Threat Precursors, Threats in Transit, Protocol Flaws, Message Confidentiality
Threats, Nonexistent and Well-Known Authentication, Spoofing, DoS, DDoS
Network Security Controls: Segmentation, Redundancy, Single Points of Failure, Encryption, Link
and End-to-End Encryption, Virtual Private Networks, VPN & Firewall, PKI and Certificates, SSL
and SSH Encryption, Kerberos, Onion Routing
UNIT II: AUTHENTICATION

Message Authentication Codes (MAC): Message Authentication Requirements, Message
Authentication Functions, Security of MACs, MACs Based on Hash Functions: HMAC.
Digital Signature: Digital Signatures, Elgamal Digital Signature Scheme, Schnorr Digital Signature
Scheme, NIST Digital Signature Algorithm, Elliptic Curve Digital Signature Algorithm, RSA-PSS
Digital Signature Algorithm.
Overview of Authentication Systems: Password-Based Authentication, Address-Based
Authentication, Cryptographic Authentication Protocols, Trusted Intermediaries, KDCs, Certification
Authorities (CAs), Session Key Establishment.
Security Handshake Pitfalls: Login, Mutual Authentication, Integrity/Encryption for Data, Two-Way
Public Key Based Authentication, One-Way Public Key Based Authentication, Mediated
Authentication (with KDC), Needham-Schroeder, Expanded Needham-Schroeder, Otway-Rees,
Nonce Types.
Strong Password Protocols: Lamport’s Hash, Strong Password Protocols, Strong Password
Credentials Download Protocols.
UNIT III: IPSEC

IPSec: Overview of IP Security (IPSec), IP Security Architecture, Modes of Operation, Security
Associations (SA), Authentication Header (AH), Encapsulating Security Payload (ESP), Comparison
of Encodings.
Internet Key Exchange (IKE): Photuris, SKIP, History of IKE, IKE Phases, Phase 1 IKE -
Aggressive Mode and Main Mode, Phase 2/Quick Mode, Traffic Selectors, The IKE Phase 1 Protocols,
Phase-2 IKE: Setting up IPsec SAs, ISAKMP/IKE Encoding - Fixed Header, Payload Portion of
ISAKMP Messages, SA Payload, SA Payload Fields.
UNIT IV: WEB SECURITY

Web Security Requirements: Web Security threats, Web traffic Security Approaches.
SSL/TLS: Secure Socket Layer (SSL), Transport Layer Security (TLS), TLS Architecture, TLS record
protocol, change cipher spec protocol, Alert Protocol, Handshake Protocol, Https, SSH.
Secure Electronic Transaction (SET): SET functionalities, Dual Signature, Roles & Operations,
Purchase Request Generation, Purchase Request Validation, Payment Authorization and Payment
Capture.
SNMP: Basic concepts of SNMP, SNMP basic components and their functionalities, Basic commands
of SNMP, SNMPv1 Community facility and SNMPv3. Intruders, Viruses and related threats.
UNIT V: FIREWALL & EMAIL SECURITY

Firewalls: Need for Firewalls, Firewall Characteristics, Types of Firewalls, Firewall Basing, Firewall
Location and Configurations.
Electronic Mail Security: Pretty Good Privacy, S/MIME, DNSSEC, Domain Keys Identified Mail.
TEXTBOOKS
1. Perlman, Radia, Charlie Kaufman, and Mike Speciner. Network security: private
communication in a public world. Pearson Education India, 2016.
2. Cryptography and Network Security – Principles and Practice: William Stallings, Pearson
Education, 6th Edition.
REFERENCES
1. Network Security and Cryptography, Bernard Menezes, CENGAGE Learning.
2. Introduction to Network Security: Neal Krawetz, CENGAGE Learning.
3. Cryptography and Network Security: Atul Kahate, Mc Graw Hill, 3rd Edition.
Credits
L T P C
CSES 315 L Network Security Lab SE 0 0 2 1

1. packet assembler/analyzer: Wireshark.
2. packet assembler/analyzer: hPing3.
3. Encrypted communication over socket using AES.
4. Message Authentication Code: MAC.
5. MAC Based on Hash Function: HMAC.
6. Session Key establishment using RSA.
7. Handcraft a TCP handshake.
8. Diffie-Hellman Algorithm.
9. DH Key exchange.
10. Network Mapper: Nmap Basics.
11. Penetration Testing: Metasploit Basics.
12. Key tool & OpenSSL.
13. One Way SSL to a Web App.
14. SNMP: net SNMP – MIB.
15. Firewall with UFW.
Credits
L T P C
CSE 410 Mobile and Wireless Security SE 3 0 0 3
UNIT I: INTRODUCTION TO MOBILE AND WIRELESS NETWORKS

IEEE wireless networks, WLAN: IEEE 802.11 (a:n), WPAN: IEEE 802.15 (Bluetooth & Zigbee),
WMAN: IEEE 802.16 (WiMAX), WMAN mobile: IEEE 802.20 (MBWA), IEEE 802.21 framework
(MIH), Cellular Networks, Cellular networks: VoIP, IMS, 4G Security
UNIT II: HOW EXISTING WIRELESS NETWORKS ARE SECURED

Attacks on wireless networks, WEP, WEP Shortcomings, IEEE 802.11i, Bluetooth, Authentication in
wireless networks, GSM Authentication, UTMS Authentication, SS7 Protocol Stack
UNIT III: NEXT GENERATION WIRELESS NETWORKS

Mobility & Internet, Mobility with MIPv6, Mobility with Mobile IPv4, IP mobility with HIP and
NetLMM, Ad Hoc Networks: Protocols, Security in Ad Hoc Networks, Key Management in Ad Hoc
Networks, Wireless Sensor Network Security, Key Management in WSN
UNIT IV: PREVENTING MALICIOUS BEHAVIOR

Naming and Addressing, Establishing Security Association: Key Establishment in Sensor Network,
Establishing Security Association: Utilizing Mobility, Wormhole Attack, Privacy in RFID System,
Location Privacy in Vehicular Network, Privacy Preserving Routing in Ad-hoc Networks
UNIT V: MOBILE APPLICATION SECURITY

Brief Introduction to Android – I, Brief Introduction to Android – II, Android Security Model
Permission, Package Management, User Management, Cryptographic Providers, Network Security
and PKI, Credential Storage, Discovering Vulnerabilities using Static Analysis, Tools Fuzzing on
Android.
TEXTBOOKS
1. Noureddine Boudriga, Security of Mobile Communications, 2010.
2. Levente Buttyán and Jean-Pierre Hubaux, Security and Cooperation in Wireless Networks,
2008. [Available Online]
REFERENCES
1. James Kempf, Wireless Internet Security: Architectures and Protocols, 2008.
2. Android Security Internals: An In-Depth Guide to Android's Security Architecture, Author:
Nikolay Elenkov, No Starch Press, First Edition, Nov. 2014
Credits
L T P C
CSE 410 L Mobile and Wireless Security Lab SE 0 0 2 1

1. Understanding IEEE 802.11with Wireshark.
2. Medium Access Control for Wirelessly Connected Stations.
3. Wireless Security – I (Wireless Security Basics).
4. Wireless Security – II (Wireless Threats).
5. Bluetooth Security.
6. Wireless Security Pen Testing (WEP, WPA/WPA2).
7. Mobility & Load and Congestion Window Size.
8. server mobility on the network performance: Load (bits/sec) , Congestion Window Size.
(bytes) , and Traffic Received (bytes).
9. Queuing Disciplines and VoIP.
10. Network Security and Virtual Private Networks.
11. Network Application Performance Analysis.
12. Connection-Oriented, Cell-Switching Technology.
13. Developing Android App.
14. Reverse Engineering using Apktool and dex2jar.
15. Analyzing Vulnerabilities using Static Analyzer and Fuzzer.
Credits
L T P C
CSE 414 Internet Protocols and Networking SE 3 0 0 3
UNIT I
Network Models: Layered Tasks, The OSI Model, Layers in OSI Model, TCP/IP Protocol suite,
Addressing. Connecting devices: Passive Hubs, Repeaters, Active Hubs, Bridges, Two Layer
Switches, Routers, Three Layer Switches, Gateway, Backbone Networks.
UNIT II
Principles of Internetworking, Connectionless Interconnection, Application-Level Interconnection,
Network Level Interconnection, Properties of the Internet, Internet Architecture, Interconnection
through IP Routers TCP, UDP & IP: TCP Services, TCP Features, Segment, A TCP Connection, Flow
Control, Error Control, Congestion Control, Process to Process Communication, User Datagram,
Checksum, UDP Operation, IP Datagram, Fragmentation, Options, IP Addressing: Classful
Addressing, IPV6.
UNIT III
Transport layer Protocols: Transport Layer Services, UDP and TCP protocols, Flow control and Error
control in Transport layer, Flow control mechanisms in Transport layer.
UNIT IV
Data Traffic, Congestion, Congestion Control, Congestion Control in TCP, Congestion Control in
Frame Relay, Source Based Congestion Avoidance, DEC Bit Scheme, Quality of Service, Techniques
to Improve QOS: Scheduling, Traffic Shaping, Admission Control, Resource Reservation, Integrated
Services and Differentiated Services.
UNIT V
Concepts of Buffer Management, Drop Tail, Drop Front, Random Drop, Passive Buffer Management
Schemes, Drawbacks of PQM, Active Queue Management: Early Random Drop, RED Algorithm.
1. Douglas. E. Comer, “Internetworking with TCP/IP “, Volume I PHI.
2. Behrouz A Forouzan, “TCP/IP Protocol Suite”, TMH, 3rd Edition.
3. B.A. Forouzan, “Data communication & Networking”, TMH, 4th Edition.
Credits
L T P C
CSE 414 L Internet Protocols and Networking Lab SE 0 0 2 1

1. Install and Configure Wired and Wireless NIC and transfer files between systems in LAN
and Wireless LAN.
2. Study basic network command and network configuration commands.
3. Configure Host IP, Subnet Mask and Default Gateway in a System in LAN (TCP/IP
Configuration).
4. Establish Peer to Peer network connection using two systems using Switch and Router in a
LAN.
5. Configure a Network topology using Packet Trace.
6. Configure Internet connection and use IPCONFIG, PING / Tracer and Net stat utilities to
debug the network issues.
7. Transfer files between systems in LAN using FTP Configuration, install Print server in a
LAN and share the printer in a network.
8. Set up a network that utilizes TCP as its end-to-end transmission protocol, and analyse the
size of the congestion window with different mechanisms.
9. Implement flow control so that a fast sender will not overrun a slow receivers' buffer.
10. Implement RED algorithm DEC Bit scheme in TCP.
11. Implement the Drop Tail Buffer Management Policies.
12. Implement the Drop Front Buffer Management Policies.
13. Implement the Random Drop Buffer Management Policies.
14. Implement the Early Random Drop Buffer Management Policies.
15. Implement RED algorithm.
Big Data and Analytics Stream
Credits
L T P C
CSE 310 Data Warehousing and Mining SE 3 0 0 3
UNIT I
Data warehousing and Online Analytical Processing: Basic concepts of Data Warehouse – Data
Warehouse Modelling – Data Warehouse Design and Usage – Data Warehouse Implementation – Data
Generalization by Attribute-oriented Induction.
UNIT II
Data Mining: Knowledge Discovery from Data – Types of Data - Data Mining Functionalities – Data
Preprocessing – Data Cleaning – Data Integration – Data Reduction – Data Transformation and Data
Discretization. Association Rule Mining – Frequent Itemset Mining methods – Pattern Evaluation
Methods.
UNIT III
Classification – Basic Concepts – Decision Tree Induction – Bayes Classification Methods – Rule
based Classification – Model Evaluation and Selection – Techniques to improve Classification
Accuracy
UNIT IV
Clustering – Cluster Analysis – Partitioning Methods – Hierarchical Methods – Density-Based
Methods – Grid Based Methods – Evaluation of Clustering.
UNIT V
Data Mining Trends and Research Frontiers - Mining Complex Data types – Other Methodologies of
Data Mining – Data Mining Applications – Data Mining and Society – Data Mining trends.
TEXTBOOKS
1. Jiawei Han, Micheline Kamber and Jian Pei “Data Mining Concepts and Techniques”, Third
Edition, Elsevier, 2011.
REFERENCES
1. G. K. Gupta “Introduction to Data Mining with Case Studies”, Third Edition, Prentice Hall of
India, 2014.
2. Pang-Ning Tan, Michael Steinbach and Vipin Kumar “Introduction to Data Mining”, Pearson
Education, 2016.
3. K.P. Soman, Shyam Diwakar and V. Ajay “Insight into Data mining Theory and Practice”,
Easter Economy Edition, Prentice Hall of India, 2006.
4. Alex Berson and Stephen J. Smith “Data Warehousing, Data Mining & OLAP”, Tata McGraw
– Hill Edition, Thirteenth Reprint 2008.
Credits
L T P C
CSE 310 L Data Warehousing and Data Mining Lab SE 0 0 2 1

1. Week 1: Implementation of OLAP operations.
2. Week 2: Data pre-processing techniques.
3. Week 3: Write a program in any programming language to generate at least 10,000 transactions
in a text file with at least three items.
4. Week 4 & 5: Write a program to implement the APRIORI algorithm.
5. Week 6 & 7: Write a program for FP-Growth algorithm.
6. Week 8 & 9: Write a program to implement Decision tree-based classification.
7. Week 10 & 11: Write a program to implement Bayesian classification.
8. Week 12: Write a program to implement K-means clustering.
9. Week 13: Write a program to implement Divisive clustering.
10. Week 14: Write a program to implement Agglomerative clustering.
11. Week 15: Write a program to implement DBSCAN clustering.
TEXTBOOKS
1. Jiawei Han, Micheline Kamber and Jian Pei “Data Mining Concepts and Techniques”, Third
Edition, Elsevier, 2011.
REFERENCES
1. G. K. Gupta “Introduction to Data Mining with Case Studies”, Third Edition, Prentice Hall of
India, 2014.
2. Pang-Ning Tan, Michael Steinbach and Vipin Kumar “Introduction to Data Mining”, Pearson
Education, 2016.
3. K.P. Soman, Shyam Diwakar and V. Ajay “Insight into Data mining Theory and Practice”,
Easter Economy Edition, Prentice Hall of India, 2006.
4. Alex Berson and Stephen J. Smith “Data Warehousing, Data Mining & OLAP”, Tata
McGraw – Hill Edition, Thirteenth Reprint 2008.
Credits
L T P C
CSE 338 Applied Data Science SE 3 0 0 3
Introduction to Data Science, Data vs. Big Data, Statistical Inference - Populations and samples,
Statistical modeling, probability distributions, fitting a model. Data Science Process, Exploratory Data
Analysis, Basic tools - plots, graphs and summary statistics of EDA. Introduction to R Programming.
UNIT II
Basic Machine Learning Algorithms - Linear Regression - K-Nearest Neighbors (K-NN) - K-means,
K-Medoids, Naive Bayes. Case Study: Real Direct (online real estate firm), Filtering Spam - Linear
Regression and K-NN and Naive Bayes for Filtering Spam. Data Wrangling: APIs and other tools for
scrapping the Web - Feature Generation and Feature Selection (Extracting Meaning from Data) -
Motivating Application and Case Study: User (customer) retention - Feature Generation - Feature
Selection algorithms – Filters; Wrappers; Decision Trees; Random Forests.
UNIT III
Recommendation Systems: Building a User-Facing Data Product - Algorithmic ingredients of a
Recommendation Engine - Dimensionality Reduction - Singular Value Decomposition - Principal
Component Analysis.
UNIT IV
Mining Social-Network Graphs - Social networks as graphs - Clustering of graphs - Direct discovery
of communities in graphs - Partitioning of graphs - Neighborhood properties in graphs.
UNIT V
Data Visualization - Basic principles, ideas and tools for data visualization – Case Study 1 on industry
projects – Case Study 2: Create Complex visualization dataset - Data Science and Ethical Issues -
Discussions on privacy, security, ethics - Next-generation data scientists.
TEXTBOOKS
1. Sinan Ozdemir, Sunil Kakade. Principles of Data Science - Second Edition Released December
2018 Publisher(s): Packt Publishing ISBN: 9781789804546.
2. Cathy O’Neil and Rachel Schutt Doing Data Science, Straight Talk from The Frontline.
O’Reilly. 2014.
REFERENCES
1. Jure Leskovek, Anand Rajaraman and Jeffrey Ullman Mining of Massive Datasets v2.1,
Cambridge University Press 2014 (free online).
2. Kevin P. Murphy. Machine Learning: A Probabilistic Perspective. ISBN 0262018020. 2013.
3. Foster Provost and Tom Fawcett. Data Science for Business: What You Need to Know about
Data Mining and Data-analytic Thinking. ISBN 1449361323. 2013.
4. Trevor Hastie, Robert Tibshirani and Jerome Friedman Elements of Statistical Learning,
Second Edition ISBN 0387952845 2009 (free online).
5. Avrim Blum, John Hopcroft and Ravindran Kannan Foundations of Data Science (Note: this
is a book currently being written by the three authors. The authors have made the first draft of
their notes for the book available online. The material is intended for a modern theoretical
course in computer science.)
6. Mohammed J. Zaki and Wagner Miera Jr. Data Mining and Analysis: Fundamental Concepts
and Algorithms. Cambridge University Press. 2014.
7. Jiawei Han, Micheline Kamber and Jian Pei Data Mining: Concepts and Techniques, Third
Edition. ISBN 0123814790 2011.
Credits
L T P C
CSE 338 L Applied Data Science Lab SE 0 0 2 1

1. Write a python program to apply datafication concepts of friendship network of your face book
account.
2. Write python program to calculate the central tendency of any popular data set. The inbuilt
functions in the python should not be used.
3. Write R – Programming to plot various charts and graphs. You have to consider minimum two
popular data sets and draw all the statistical observations.
4. Write a python Program to apply EDA on any two popular data sets and provided your analysis
and interpretations. Use matplotlib library of python along with other libraries for the analysis
and interpretation.
5. Write Python program to implement Linear Regression using inbuilt python Library. Also,
write your own program to implement Linear Regression without using the inbuilt function.
Compare and contrast the results.
6. Write Python program to implement K-Nearest Neighbors using inbuilt python Library. Also,
write your own program to implement K-Nearest Neighbors without using the inbuilt function.
Compare and contrast the results.
7. Write Python program to implement K-Means using inbuilt python Library. Also, write your
own program to implement K-Means without using the inbuilt function. Compare and contrast
the results.
8. Write a python program to implement a Spam Filter using Linear Regression and K-NN. Use
a popular dataset.
9. Write a Python Program to Scrapping the Web using suitable API. Create a usable dataset for
classification and clustering purpose.
10. Write a python program to generate the features from the data set created by you for exercise
9.
11. Write a Python Program to implement Filter and Wrappers.
12. Write a Python Program to implement Decision Trees, Random Forests – The inbuilt functions
should not be used for the implementation.
13. Write a python Program to implement Singular Value Decomposition and Principal
Component Analysis. Use any popular data set.
14. Write a python Program to extract the friendship details of your face book account as Social
network Graph and represent in various visual forms.
15. Write a python program to extend the above exercise to discover the communities in the graph,
partition the graph and extracting the neighbor hood properties of the graphs.
16. Write Python Program using Bokeh 2.1.1 realize the all the basic principles of data
visualization.
17. Consider any popular dataset and present complex visualization principle using Bokeh 2.1.1.
Credits
Course Code Course Name Course Category L T P C
CSE 417 Principles of Big Data Management SE 3 0 0 3
UNIT I
Understanding Big Data – Concepts and Terminology – Big Data Characteristics – Different types of
Data – Big Data Storage concepts – Clusters – File systems and distributed file systems – NoSQL –
Sharding – Replication – CAP theorem – BASE - Hadoop Distributed File System (HDFS)
Architecture - HDFS commands for loading/getting data - Accessing HDFS through Java program.
UNIT II
Big Data Processing Concepts – Parallel Data Processing – Distributed Data Processing – Hadoop –
Processing workloads – Batch processing with MapReduce – Map and Reduce Tasks – MapReduce
Example
UNIT III
Hadoop ecosystem and its components– Flume - Sqoop - Pig - Spark - Hbase.
UNIT IV
Querying big data with Hive: Introduction to Hive QL - Hive QL: data definition- data manipulation
– Hive QL Queries.
UNIT V
Data Analytics using R: Introduction to R, Creating a dataset, Getting started with graphs, Basic data
management, Advanced data management.
1. Big Data Fundamentals: concepts, Drivers and Techniques: Person Education, 2016
2. Hadoop The Definitive Guide, IV edition, O’Reilly publications
3. Hadoop in Action, Chuck lam, Manning publications
4. Programming, Hive, O’Reily publications,
5. Apache Hive Cookbook, PACKT publications
6. R in Action, Robert I. Kabacoff, Manning publications
7. Practical Data Science with R, Nina Zumel John Mount, Manning publications.
Credits
L T P C
CSE 417 L Principles of Big Data Management Lab SE 0 0 2 1

1.a. Hadoop Installation
b. Hadoop Shell Commands
2.a. Writing a file from local file system to Hadoop Distributed file system (HDFS)
b. Reading a file from HDFS to the local file system.
3.a. Implementation of Word Count program using MapReduce without combiner logic.
b. Implementation of Word Count program using MapReduce with combiner logic.
4.Weather data analysis for analyzing hot and cold days using MapReduce.
5. Implementation of MapReduce algorithm for Matrix Multiplication.
6. Implement a MapReduce program to identify “common friends” among all pairs of users.
7. Transfer data between Hadoop and relational database servers using Sqoop.
8. Read a text file from HDFS into RDD using Spark.
9. Use HiveQL to analyze the stock exchange dataset and calculate the covariance between the stocks
for each month. This will help a stock-broker in recommending the stocks to his customers.
10. Implement JOINS using HIVE
a. Inner Join
b. Left outer join
c. Right outer Join
d. Full outer join
11. Write a R program to create a student record using the Vector concept.
12. Write a R program to create medical patients status using data frame
i) Patient age ii) Gender iii) Symptoms iv) Patient Status
13. Write a R program to visualize student marks of various subjects using Bar-chart and Scatter plot
Credits
L T P C
CSE 419 Information Retrieval SE 3 0 0 3
UNIT I
Introduction to information retrieval, IR problem, IR system, The Web, Search interface, Visualizing
search interface, Inverted index and boolean queries, Tokenization, Stemming, Stop words, Phrases,
Phrases queries, Index construction, Index compression, k-gram indexes
UNIT II
Retrieval models: Boolean, Vector space model, TF-IDF, The cosine measure, Document length
normalization, Probabilistic models, Binary Independence Model, Okapi, Language modeling,
Evaluating IR system: User happiness, Precision, Recall, F-measure, E-measure, Normalized recall,
Evaluation problems
UNIT III
Relevance feedback and Query expansion: Explicit relevance feedback, Explicit relevance feedback
through clicks, Implicit feedback through local analysis, Implicit feedback through global analysis
Document format, Markup language, Text properties, Document processing, Document organization,
Text compression, Query languages, Query properties
UNIT IV
Text/Document classification, Clustering and LSI: Introduction to classification, Naive Bayes models,
Rocchio classification, k-Nearest Neighbors, Support vector machine classifiers, Decision trees,
Bagging, Boosting, Choosing right classifier
Introduction to clustering, Evaluation of clustering, k-means clustering, Hierarchical agglomerative

clustering, Divisive clustering; Low-rank approximations, Latent semantic indexing
UNIT V
Web IR: Hypertext, Web crawling, Indexes, Search engines, Ranking, Link analysis, Page Rank, HITS
TEXTBOOKS & REFERENCES

1. Modern Information Retrieval: The Concepts and Technology Behind Search, by Ricardo
Baeza-Yates and Berthier Ribeiro-Neto, Second Edition (Pearson Education India, 2010)
2. Introduction to Information Retrieval, by C. Manning, P. Raghavan, and H. Schütze
(Cambridge University Press, 2008)
3. Mining the Web, by S. Chakrabarti (Morgan-Kaufmann, 2002)
4. Natural Language Processing And Information Retrieval, by Tanveer Siddiqui and U. S.
Tiwary, First Edition (Oxford University Press, 2008)
Credits
CSE 419 L Information Retrieval Lab SE 0 0 2 1

1. Tokenization, Stemming, Stop words removal, Inverted index construction - Token sequence,
Sort, Dictionary & Postings, Implementation of Boolean queries.
2. Ranked retrieval - Implementation of TF-IDF, Vector space model, Cosine similarity.
3. Ranked retrieval - Implementation of Binary Independence Model, Okapi BM25.
4. Implementation of Text/Document classification algorithms - Naive Bayes models, Rocchio
classification, k-Nearest Neighbors, Support vector machine classifiers, Decision trees,
Bagging, Boosting.
5. Implementation of Text/Document clustering algorithms - k-means clustering, Hierarchical
agglomerative clustering, Divisive clustering.
6. Implementation of Low-rank approximations, Latent semantic indexing.
7. Sort-based index construction.
8. Implementation of External memory indexing - BSBI, SPIMI.
9. Implementations of Dynamic indexing - Logarithmic merge.
10. Dictionary compression - Implementation of Blocking, Posting Compression -
Implementation of Gamma codes.
11. Development of a Web Crawler and a small-scale web search engine - Ranking, PageRank,
HITS.
Distributed and Cloud Computing
Credits
L T P C
CSE 316 Distributed Systems SE 3 0 0 3
UNIT I: INTRODUCTION AND ARCHITECTURES

Introduction: Definition of a distributed system, Goals, types of distributed systems Architectures:
Architecture styles, System architectures, Architectures versus middleware, Self-management in
distributed systems.
UNIT II: PROCESSES AND COMMUNICATION

Processes: Threads, Virtualization, Clients, Servers, Code Migration. Communication: Fundamentals,
Remote Procedure Call, Message and Stream oriented communication, Multicast communication.
UNIT III: NAMING AND SYNCHRONIZATION

Naming: Flat naming, Structured naming, Attribute-based naming. Synchronization: Clock
synchronization, Logical clocks, Mutual exclusion, Election algorithms.
UNIT IV: CONSISTENCY AND REPLICATION

Replication as Scaling Technique, Data-Centric Consistency Models: Continuous Consistency, Data-
Centric Consistency Models: Consistent Ordering of Operations, Data-Centric Consistency Models:
Consistent Ordering Of Operations, Replica-Server Placement, Replica-Server Placement, Content
Distribution, Continuous Consistency, Primary-Based Protocols, Replicated-Write Protocols, Cache-
Coherence Protocols.
UNIT V: FAULT TOLERANCE AND SECUIRTY

Fault tolerance: Introduction, Process Resilience, Reliable client server communication, Reliable
group communication, Distributed Commit, Recovery. Security: Secure channels, Access control,
Security Management.
1. Andrew S. Tanenbaul, Maarten Van Steen, Distributed Systems, Principles and Paradigms,
Pearson publications, 2nd edition.
2. Pradeep K Sinha, “Distributed Operating Systems: Concepts and Design”, Prentice Hall of
India, 2007.
3. George Coulouris, Jean Dollimore and Tim Kindberg, “Distributed Systems Concepts and
Design”, Fifth Edition, Pearson Education, 2012.
4. Liu M.L., “Distributed Computing, Principles and Applications”, Pearson Education, 2004.
\
Credits
L T P C
CSE 316 L Distributed Systems Lab SE 0 0 2 1

1. Experiment-1: Implement concurrent echo client-server application.
2. Experiment -2: Implement concurrent day-time client-server application.
3. Experiment-3: Configure following options on server socket and tests them: SO_KEEPALIVE,
SO_LINGER, SO_SNDBUF, SO_RCVBUF, TCP_NODELAY
4. Experiment -4: Simulate the functioning of Lamport‟s Logical Clock in C.
5. Experiment -5: Simulate the Distributed Mutual Exclusion in C.
6. Experiment -6: Implement Java RMI‟ mechanism for accessing methods of remote systems.
7. Experiment -7: Simulate Balanced Sliding Window Protocol in C.
8. Experiment -8: Incrementing a counter in shared memory.
9. Experiment -9: Create CORBA based server-client application.
10. Experiment -10: Design XML Schema and XML instance document.
11. Experiment -11: SOAP based: Implement Arithmetic Service that implements add and subtract
operations /Java based: Implement Trigonometric Service that implements sin, and cos
operations.
Credits
L T P C
CSE 318 Cloud Computing SE 3 0 0 3
UNIT I
Distributed system models: Scalable computing over the internet, Technologies for network-based
systems, System models and software environments for distributed and cloud computing, performance,
security and Energy Efficiency Computer clusters for Scalable parallel computing: Clustering for
Massive parallelism, Computer clusters and MPP Architectures, Design principles of computer
clusters, Cluster job and resource management.
UNIT II
Virtual Machines and Virtualization of Data Centres: Implementation levels of virtualization,
Virtualization structures, tools and mechanisms, Virtualization of CPU, Memory and I/O devices,
Virtual clusters and resource management, Virtualization for Data center automation.

Cloud computing and service models, Data center design and interconnection networks, Architectural
design of Compute and storage clouds, Public cloud platforms, Inter-cloud resource management,
Cloud security and trust management.

Services and service-oriented architecture, Message oriented middleware, Portals and science
gateways, Discovery, Registries, Meta data and databases. Workflow in service-oriented architectures,
UNIT V: FAULT TOLERANCE AND SECURITY

Features of cloud and Grid platforms, Parallel and distributed programming paradigms, Programming
support for Google application engine, Programming on Amazon AWS and Microsoft Azure,
Emerging cloud software environments.
TEXTBOOKS
1. Cloud Computing, Theory and Practice, Dan C Marinescu, MK Elsevier.
2. Cloud Computing: Principles and Paradigms, Rajkumar Buyya, James Broberg, Andrzej M.
Goscinski, Wiley.
REFERENCES
1. Distributed and Cloud Computing. Kal Hwang. Geoffeiy C. Fox. Jack J. Dongarra. Elsevier.
2012.
2. Cloud computing, Black book. Deven Shah, Kailash Jayaswal, Donald J. Houde, Jagannath
Kallakurchi.
3. Cloud Computing: Concepts, Technology & Architecture (The Prentice Hall Service
Technology Series from Thomas Erl) 1st Edition, Thomas Erl (Author), Ricardo
Puttini , Zaigham Mahmood.
Credits
L T P C
CSE 318 L Cloud Computing Lab SE 0 0 2 1

1. Basics of Virtualization: VMM, Example of VMM (virtualbox), Cretaion of a VM,
Networking and communication between VMs.
2. Introduction to CloudSim: Installation and Execution, Cloud Datacenter, Network Topology.
3. Simulation of a Cloud Framework: Creating a DC, Creation of Tasks, Creation of VMs,
Defining task and VM characteristics, execution of tasks on VMs.
4. Scalable and dynamic Cloud systems: Creation of scalable cloud entities, creation of dynamic
entities.
5. Resource Allocation in Cloud Datacenter: Experimenting and understanding various resource
allocation policies, Changing the resource allocation policy, effects of resource allocation
policies.
6. Power Management in Cloud Datacenters: Creation of a power datacenter, understanding
various power saving techniques.
7. Understanding Commercial Cloud Frameworks: Amazon AWS, Elastic Cloud, Amazon Load
Balancer, creating VMs, Allocation of Resources.
Credits
L T P C
CSE 416 Cloud Data Management SE 3 0 0 3
UNIT I
Distributed File system: Architecture: Client-Server Architectures, Cluster-Based Distributed File
Systems, Symmetric Architectures, Processes, Communication, Naming, Synchronization,
Consistency and replication, Fault tolerance, Security
UNIT II
Distributed data management: distributed systems, peer to peer systems, database systems,
Overview of key value stores and examples, Design choices and their implementations.
Transactions on co-located data: Data ownership, Transaction execution, Data storage, Replication, A
survey of the systems.
UNIT III
Cloud Data Management: Database like functionality in cloud storage, Transactional support for
geo-replicated data, Incremental update processing using distributed transaction, Scalable distributed
synchronization using mini transactions. Multi-tenant database systems: Multitenancy models,
database elasticity in the cloud, Autonomic control for data base workloads in the cloud.
UNIT IV
Azure database service platform: Understanding the Service, Designing SQL Database, Migrating
an Existing Database, Using SQL Database, Scaling SQL Database, Governing SQL Database.
MySQL and PostgreSQL
UNIT V
SQL server 2017: Hybrid cloud features, migrate databases to Azure IaaS, Run SQL Server
on Microsoft Azure Virtual Machines, Considerations on High Availability and Disaster Recovery
Options with SQL Server on Hybrid Cloud and Azure IaaS, Working with NoSQL Alternatives.
TEXTBOOKS
1. Data management in the cloud: challenges and opportunities: Divyakant Agrawal, Sudipto
das, Amr EI Abbadi, 2013.
2. Cloud data design, Orchestration and Management using Microsoft Azure, Francesco Diaz
Roberto Freato, Apress, Springer publications, 2018.
REFERENCES
Pearson publications, 2 edition.
nd
2. Cloud data design, Orchestration and Management using Microsoft Azure, Francesco Diaz
Roberto Freato, Apress, Springer publications, 2018.
3. Cloud database development and Management, Lee chao, CRC Press, Taylor and Francis
group. 2014.
4. Cloud data management, Liang Zhao, Sherif Sakr, Anna Liu, Athman Bouguettaya,
Springer publications, 2014.
Credits
L T P C
CSE 416 L Cloud Data Management Lab SE 0 0 2 1
LIST OF PRACTICALS EXPERIMENTS

1. Week 1: Designing SQL Database in Azure
Using Database Projects (or other similar tools) to create and manage the development of
the database.
Connection modes:
• outside Azure
• inside Azure
2. Week 2: SQL Database Options
Aanalyze the various SQL database options: Single Database with a Single Schema, Single
Database with Different Schemas and other
3. Week 3: Indexes
Index creation, Index evaluation, Index management for a table
Automatic Tuning
4. Week 4: Migration
Migrate an existing SQL Server database to Azure SQL Database.
a. Preparing the Database
b. Moving the Database
c. Exporting the DB
5. Week 5: Scaling
Dynamically scale database resources with minimal downtime
6. Week 6: Governing SQL Database
Value-added services of SQL Database
a. Authentication
b. Firewall
c. Encryption
7. Week 7: Encryption
Apply different database encryption methods to a database.
a. Transparent Data Encryption
b. Always Encrypted
c. Dynamic Data Masking
Explore different backup and monitoring options of Azure Databases
8. Week 8: SQL Server 2017
Connect to SQL Server instance
a. Create a database
b. Create tables under the database
9. Week 9: Azure Storage
Create a Storage Account in Azure portal
Add a managed data disk to a SQL Server virtual machine
10. Week 10: Backup on Azure
Create SQL Server Backup to URL.
11. Week 11: Backup on Azure
Create a SQL Server Managed Backup to Microsoft Azure.
Take snapshots of data and log files that are placed into Azure Storage using File-Snapshots
Backups.
12. Week 12: Restore
Create a SQL Server Managed Backup to Microsoft Azure feature.
Access backup data from Azure Storage taken using SQL Server Managed Backup and Restore
it.
13. Week 13:
Use Azure Storage to host SQL Server Database Files and Use Azure Snapshots
14. Week 14:
Migrate a Database Using the Data-Tier Application Framework
15. Week 15:
Use Azure Storage to host SQL Server Database Files and Use Azure Snapshots
Explore the High Availability and Disaster Recovery Options with SQL Server
On Hybrid Cloud and Azure IaaS
1. Cloud data design, Orchestration and Management using Microsoft Azure, Francesco
Diaz Roberto Freato, Apress, Springer publications, 2018.
2. “Design a relational database in Azure SQL Database using SSMS”,
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-design-first-database
3. “Data Migration Assistant, https://www.microsoft.com/en-
us/download/details.aspx?id=53595
4. “Dynamically scale database resources with minimal downtime”,
https://docs.microsoft.com/en-us/azure/azure-sql/database/scale-resources
Credits
L T P C
CSE 418 Service Oriented Computing SE 3 0 0 3
UNIT I: WEB SERVICE FUNDAMENTALS

Introduction to Web Services - fundamental of web services, basic operational model of web
services, Business motivations for web services, B2B, B2C, Technical motivations, basic steps of
implementing web services, benefits and challenges of using web services, tools and technologies
enabling web services, Web services Architecture and its characteristics, web services
communication models, core building blocks of web services, web services technology stack.
Orchestration, Choreography. Service layer Abstraction - Application Service Layer, Business
Service Layer, Orchestration Service Layer.
UNIT II: SERVICE ORIENTED ARCHITECTURE

Service–oriented Architecture (SOA), implementation view, logical view, process view, deployment
view, composition of web services, from application server to peer to peer, life in the runtime.
Characteristics of SOA, Comparing SOA to client-server and distributed internet architectures,
Anatomy of SOA, How components in an SOA interrelate. Fundamentals of SOAP-SOAP Message
Structure, SOAP encoding, Encoding of different data types, SOAP communication and messaging,
SOAP message exchange models, limitations of SOAP. REST Protocol, SOAP vs REST.
UNIT III: SERVICE ORIENTED PLATFORMS

WSDL, Anatomy of WSDL, manipulating WSDL, web service policy, UDDI, Anatomy of UDDI,
UDDI- UDDI registries, uses of UDDI Registry, UDDI data structures, Programming with UDDI,
Publishing, searching and deleting information in a UDDI Registry, Publishing API, limitations of
UDDI, Discovering Web Services, service discovery mechanisms, role of service discovery in a SOA,
Service Selection. SOA support in J2EE: Java API for XML based web services (JAX-WS), Java
architecture for XML binding (JAXB), Java API for XML Registries (JAXR), Java API for XML
based RPC (JAXRPC), Web Services Interoperability Technologies (WSIT). SOA support in .NET:
Common Language Runtime, ASP.NET web forms, ASP.NET web services, Web Services
Enhancements (WSE).
UNIT IV: APPLICATION DEVELOPMENT USING OPEN STACK

Understanding Open stack eco system: Open stack Heat, Open stack Database As A Service: Trove,
Designate: Dns As A Service, Magnum, Murano: Application As A Service, Ceilometer: Telemetry
As A Service, Application development and deployment in Open stack: Building applications from
the scratch, converting legacy applications into Open stack applications. Event Driven Programs with
Cloud.
UNIT V: MONITORING AND METERING

Monitoring and metering, Updating and patching. Kubernetes: Concepts, Cluster Architecture,
Containers and Dockers, Workloads, Services, Load Balancing, and Networking, Policies,
Scheduling and Eviction, Cluster Administration. Apigee Edge, API development lifecycle.
TEXTBOOKS
1. Service-Oriented Architecture: Concepts, Technology, and Design By Thomas Erl, Pearson
Education India.
2. OpenStack Cloud Application Development by Scott Adkins, John Belamaric, Vincent
Giersch, Denys Makogon, Jason E. Robinson, Wrox.
3. Mastering kubernetes: Sayfan, Gigi, Packt Publishing Ltd.
REFERENCES
1. Service Oriented Computing: Semantics, Processes, Agents: Munindar Singh & Michael
Huhns, Wiley Publication.
2. Enterprise SOA Designing IT for Business Innovation: Dan Woods and Thomas Mattern ,
O’REILLY.
3. Service-oriented Architecture for Enterprise Applications: Shankar Kambhampaty, John
Wiley & Sons.
4. SOA using Java™ Web Services: Mark D Hansen, Prentice Hall Publication.
Credits
L T P C
CSE 418 L Service Oriented Computing Lab SE 0 0 2 1

Develop Java Based Program using JAXP or XML API in reading XML file for Students
Information and Display HTML Table.
1. Develop Java Based web Service using REST and SOAP Based web service in Netbeans for
University Course List and Search Course based Course Title and Course ID.
2. Create web calculator service in .NET Beans and create Java client to consume this web
service.
3. Develop same web service using JX-WS.
4. Create web calculator service in .NET and Create java client to consume web service.
developed using Apache AXIS.
5. Using WS –GEN and WS-Import develop the java web service & call it by Java Client.
6. Open stack Heat.
7. Opens tack Database As A Service: Trove.
8. Designate: DNS As A Service.
9. Magnum.
10. Murano: Application As A Service.
11. Building applications from the scratch.
12. converting legacy applications into Open stack applications.
13. Kubernetes: Containers and Dockers.
14. Kubernetes: Load Balancing, Scheduling.
Internet of Things (IoT) Stream
Credits
L T P C
CSES 337 Cryptography SE 3 0 0 3
UNIT I
History and overview of cryptography, Classical Encryption Techniques: Symmetric Cipher Model,
Substitution Techniques, Transposition Techniques, Rotor Machines, And Steganography
UNIT II
Stream Ciphers and Block Ciphers, Attacks on block ciphers, Block Cipher Principles, The Data
Encryption Standard (DES), Block Cipher Design Principles, Group, Rings, Field, Polynomial
Arithmetic, The Euclidean Algorithm, Finite Fields of the Form GF(2n)
UNIT III
Advanced Encryption Standard (AES), Stream Ciphers, RC4, The Chinese Remainder Theorem,
Public Key Cryptography and RSA Algorithm, Diffie-Hellman Key Exchange, Elliptic Curve
Cryptography.
UNIT IV
Cryptographic Hash Functions: Applications of Cryptographic Hash Functions, Two Simple Hash
Functions, Requirements and Security, Secure Hash Algorithm (SHA), SHA-3.
UNIT V
Introduction to Block Chain, Bitcoin basics, Smart Contracts, Blockchain development platforms and
APIs, Blockchain Ecosystems, Ethereum, Distributed Consensus, Blockchain Applications
1) Stallings, William. Cryptography and network security, Principle and Practice. Pearson
2) R. Stinson Cryptography, Theory and Practice (Fourth Edition Edition)
3) Handbook of Applied Cryptography by A. Menezes, P. Van Oorschot, S. Vanstone.
4) Melanie Swan, Blockchain, Blueprint for a new Economy, OReilly
Credits
L T P C
CSE 337 L Cryptography Lab SE 0 0 2 1

1. Write a program take text file as an input and print word, character count and ascii value of
each characters as output. (Hint: Use open(), read() and split()).
2. Write a encryption program: Input: computerscienceengineeringsrmuniversity Output:
gsqtyxivwgmirgiirkmriivmrkwvqyrmzivwmxc Hint: key =4 (play with ascii value).
3. Raju send an encrypted message (cipher text) “PHHW PH DIWHU WKH WRJD SDUWB” to
Rani. Can you build decryption process and find out what is the message (plain text) send to
Rani? Hint: try all keys.
4. Raju send encrypted message “ZICVTWQNGKZEIIGASXSTSLVVWLA” to Rani. Can you
build decryption process and find out what is the message send to Rani. Hint: try all keys for
each character.
5. Kohli have plain text “wewishtoreplaceplayer”. Can you build encryption process and find out
what is the cipher text he needs send to BCCI. Help him out by using monoalphabatic cipher.
Hint: use any one-to-one mapping between alphabets.
One to one
mapping
6. Kohli sent encrypted message (Cipher text) “SEEMSEAOMEDSAMHL” to Anushka. Can you
build decryption process and find out what is the message (plain text) send to Anushka. Hint:
use above one to one mapping between alphabets.
7. Raju want to build encrypted and decryption algorithms of Playfair Cipher. Help him to build
a key matrix using the key “srmapuniversity”
8. By using key matrix Raju want to send message “we are discovered save yourself” to Rani.
Can you build encryption process and find out what is the cipher text message send to Rani by
using palyfaircipher.
9. By using key “CBDE” Raju would like send message (plain text)“HELLO WORLD” to Rani.
Can you build encryption process and find out what is the encrypted message (cipher text) to
Raju by using Hill Cipher.Also Can you build decryption process and find out what is the decrypted
message (plain text) of cipher text "SLHZYATGZT" by using Hill Cipher.
10. Implementation of Encryption and Decryption of Vigenère Cipher
keyword deceptive
key: deceptivedeceptivedeceptive
plaintext: wearediscoveredsaveyourself
ciphertext: ZICVTWQNGRZGVTWAVZHCQYGLMGJ
11. Implement the Encryption and Decryption of Row Transposition.
Key: 4312567
Plaintext: a t t a c k p
ostpone
duntilt
woamxyz
Ciphertext: TTNAAPTMTSUOAODWCOIXKNLYPETZ
12. Implement the Euclidean Algorithm for integers and polynomials.
13. Implement AES Key Expansion.
14. Implementation of AES encryption and decryption
15. Implementation of Simplified DES Encryption and decryption
16. Implementation of RC4
17. Implementation of RSA algorithm
18. Implementation of Diffie-Helman key exchanges
19. Implementation of elliptic-curve cryptography
20. Implementation of Hash functions
Credits
L T P C
CSE 318 Cloud Computing SE 3 0 0 3
UNIT I
Distributed system models: Scalable computing over the internet, Technologies for network-based
systems, System models and software environments for distributed and cloud computing, performance,
security and Energy Efficiency Computer clusters for Scalable parallel computing: Clustering for
Massive parallelism, Computer clusters and MPP Architectures, Design principles of computer
clusters, Cluster job and resource management.
UNIT II: PROCESSES AND COMMUNICATION

Virtual Machines and Virtualization of Data Centres: Implementation levels of virtualization,
Virtualization structures, tools and mechanisms, Virtualization of CPU, Memory and I/O devices,
Virtual clusters and resource management, Virtualization for Data center automation.

Cloud computing and service models, Data center design and interconnection networks, Architectural
design of Compute and storage clouds, Public cloud platforms, Inter-cloud resource management,
Cloud security and trust management.

Services and service-oriented architecture, Message oriented middleware, Portals and science
gateways, Discovery, Registries, Meta data and databases. Workflow in service-oriented architectures.
UNIT V: FAULT TOLERANCE AND SECURITY

Features of cloud and Grid platforms, Parallel and distributed programming paradigms, Programming
support for Google application engine, Programming on Amazon AWS and Microsoft Azure,
Emerging cloud software environments.
TEXTBOOKS
1. Cloud Computing, Theory and Practice, Dan C Marinescu, MK Elsevier
2. Cloud Computing: Principles and Paradigms, Rajkumar Buyya, James Broberg, Andrzej M.
Goscinski, Wiley.
REFERENCES
1. Distributed and Cloud Computing. Kal Hwang. Geoffeiy C. Fox. Jack J. Dongarra. Elsevier.
2012.
2. Cloud computing, Black book. Deven Shah, Kailash Jayaswal, Donald J. Houde, Jagannath
Kallakurchi.
3. Cloud Computing: Concepts, Technology & Architecture (The Prentice Hall Service
Technology Series from Thomas Erl) 1st Edition, Thomas Erl (Author), Ricardo
Puttini , Zaigham Mahmood.
Credits
L T P C
CSE 318 L Cloud Computing Lab SE 0 0 2 1

1. Basics of Virtualization: VMM, Example of VMM (virtual box), Creation of a VM,
Networking and communication between VMs.
2. Introduction to Cloud Sim: Installation and Execution, Cloud Data centre, Network
Topology,
3. Simulation of a Cloud Framework: Creating a DC, Creation of Tasks, Creation of VMs,
Defining task and VM characteristics, execution of tasks on VMs.
4. Scalable and dynamic Cloud systems: Creation of scalable cloud entities, creation of dynamic
entities.
5. Resource Allocation in Cloud Data centre: Experimenting and understanding various
resource allocation policies, Changing the resource allocation policy, effects of resource
allocation policies.
6. Power Management in Cloud Data centres: Creation of a power data centre, understanding
various power saving techniques.
7. Understanding Commercial Cloud Frameworks: Amazon AWS, Elastic Cloud, Amazon Load
Balancer, creating VMs, Allocation of Resources.
Credits
L T P C
CSE 317 Embedded Systems SE 3 0 0 3
UNIT I: INTRODUCTION TO EMBEDDED SYSTEMS

Introduction, characteristics of embedding computing applications, concept of real time systems,
designing of hardware and software components, challenges in embedded system design, Safety and
Security of an Embedded System, Performance of Embedded Systems.
UNIT II: INSTRUCTION SET OF PROCESSORS

Overview of various features of Computer Architecture, Instruction-set of ARM family of processors,
Instruction-set of PIC family of Processors, Digital Signal Processor, Instruction set of TI C55X DSP.
Programmed I/O, Interrupts (supported by Arm, PIC , TI C55x family of processors), Supervisor mode,
exceptions, traps, co-processors, memory system, CPU power management.
UNIT III: INPUT-OUTPUT SUB-SYSTEM

I/O sub-system: busy-wait I/O, DMA, interrupt driven I/O, co-processors and hardware accelerators,
Timers and counters, watchdog timers, interrupt controllers, DMA controllers, A/D and D/A
converters. Component interfacing, interfacing protocols, Firewire, USB, IrDA. Sensors and
Actuators.
UNIT IV: PROGRAM DESIGN AND ANALYSIS

State machine, circular buffer, stream-oriented programming, data flow graph (DFG), control flow
graph (CFG), Compilation techniques, performance analysis, performance optimization, power
analysis and power optimization, program validation and testing.
UNIT V: OPERATING SYSTEMS

Basic features of an operating system, Kernel features, polled loops system, co-routines, interrupt-
driven system, multi-rate system, processes and threads, context switching, scheduling, task
assignment, inter-process communication, Real-time Memory Management: Process stack
management, dynamic allocation, synchronous and asynchronous I/O, Interrupt handling, device
drivers, example real-time OS: VxWorks, RT-Linux, PSOS.
TEXTBOOKS
1. Wolf, Marilyn. Computers as components: principles of embedded computing system design.
Elsevier, 2017 (4th Ed.).
2. Marwedel, Peter. Embedded System Design: Embedded Systems Foundations of Cyber-
Physical Systems, and the Internet of Things. Springer, 2017. (3rd Ed.)
REFERENCES
1. Manish Patel, The 8051 Microcontroller based Embedded System, McGraw Hill 2014 (1st
edn.).
2. Mall, Rajib. Real-time systems: theory and practice. Pearson Education India, 2009. (1st
edn.).
Credits
L T P C
CSE 317 L Embedded Systems Lab SE 0 0 2 1

1. Introduction to Software tool (preferably kiel MDK Microcontroller Development Kit) used
in the lab. (2 hrs)
2. Interfacing of 8-bit ADC 0809 with 8051 Microcontroller. (1 hour)
3. Interfacing of 8-bit DAC 0800 with 8051 Microcontroller. (1 hour)
4. Implementation of Serial Communication by using 8051 serial ports. (1 hour)
5. Interfacing of individual LEDs and program them to blink after a fixed time interval. (1 hour)
6. Interfacing of 16*2 LCD panel with 8051 Microcontroller. (1 hour)
7. Interfacing of stepper motor with 8051 Microcontroller. (1 Hour)
8. A minor project is given to student to implement (7 hrs)
Credits
L T P C
CSE 319 IoT Design Protocols SE 3 0 0 3
UNIT I: OVERVIEW
IoT-An Architectural Overview– Building an architecture, Main design principles and needed
capabilities, An IoT architecture outline, standards considerations. M2M and IoT Technology
Fundamentals- Devices and gateways, Local and wide area networking, Data management, Business
processes in IoT, Everything as a Service (XaaS), M2M and IoT Analytics, Knowledge Management.
UNIT II: REFERENCE ARCHITECTURE

IoT Architecture-State of the Art – Introduction, State of the art, Reference Model and architecture,
IoT reference Model - IoT Reference Architecture- Introduction, Functional View, Information View,
Deployment and Operational View, Other Relevant architectural views. Real-World Design
Constraints- Introduction, Technical Design constraints-hardware is popular again, Data
representation and visualization, Interaction and remote control.
UNIT III: IOT DATA LINK LAYER & NETWORK LAYER PROTOCOLS
PHY/MAC Layer (3GPP MTC, IEEE 802.11, IEEE 802.15), Wireless HART, Z-Wave, Bluetooth
Low Energy, Zigbee Smart Energy, DASH7 - Network Layer-IPv4, IPv6, 6LoWPAN, 6TiSCH, ND,
DHCP, ICMP, RPL, CORPL, CARP
UNIT IV: TRANSPORT & SESSION LAYER PROTOCOLS

Layer (TCP, MPTCP, UDP, DCCP, SCTP)-(TLS, DTLS) – Session Layer-HTTP, Co AP, XMPP,
AMQP, MQTT.
UNIT V: SERVICE LAYER PROTOCOLS & SECURITY

Service Layer -oneM2M, ETSI M2M, OMA, BBF – Security in IoT Protocols – MAC 802.15.4,
6LoWPAN, RPL, Application Layer.
1. Jan Holler, Vlasios Tsiatsis, Catherine Mulligan, Stefan Avesand, Stamatis Karnouskos,
2. David Boyle, “From Machine-to-Machine to the Internet of Things: Introduction to a New Age
of Intelligence”, 1st Edition, Academic Press, 2014.
3. Peter Waher, “Learning Internet of Things”, PACKT publishing, BIRMINGHAM –
4. MUMBAI
5. Bernd Scholz-Reiter, Florian Michahelles, “Architecting the Internet of Things”, ISBN 978-3-
642-19156-5 e-ISBN 978-3-642-19157-2, Springer
6. Daniel Minoli, “Building the Internet of Things with IPv6 and MIPv6: The Evolving World of
M2M Communications”, ISBN: 978-1-118-47347-4, Willy Publications Vijay Madisetti and
Arshdeep Bahga, “Internet of Things (A Hands-on-Approach)”, 1st Edition, VPT, 2014.
7. http://www.cse.wustl.edu/~jain/cse570-15/ftp/iot_prot/index.html
Credits
L T P C
CSE 319 L IoT Design Protocols Lab SE 0 0 2 1

Week1:
1. Study and Install IDE of Arduino and different types of Arduino Boards like Arduino uno,
Arduino NG REV-C , Arduino NANO .
Week 2:
2. Write program using Arduino IDE for Blink LED.
Hardware Requirements:
1x Breadboard
1x Arduino Uno R3
1x RGB LED
1x 330Ω Resistor
2x Jumper Wires
Blinking the RGB LED:

With a simple modification of the breadboard, we could attach the LED to an output pin of the
Arduino. Move the red jumper wire from the Arduino 5V connector to D13.
Week 3:
3. Develop a program using Arduino IDE and Arduino Board for RGB Led.
1x Breadboard
1x Arduino Uno R3
1x LED
1x 330Ω Resistor
2x Jumper Wires
Blinking the LED

With a simple modification of the breadboard, we could attach the LED to an output pin of the
Arduino. Move the red jumper wire from the Arduino 5V connector to D13.
Week 4:
4. Study the temperature Sensors and write a program using Arduino IDE and Arduino Board for
Temperature Sensor.
Weeks 5:
5. Study and Implement RFID, NFC using Arduino.
1 x Arduino UNO or 1 x Starter Kit for Raspberry Pi + Raspberry Pi
1 x Communication Shield
1 x RFID 13.56 MHz / NFC Module for Arduino and Raspberry Pi
1 x Mifare tag (card/keyring/sticker)
1 x PC
Weeks 6:
6. Write programs using Arduino IDE and Arduino Board for MQTT Protocol.
Weeks 7:
7. Write a program to Study and Configure Raspberry Pi.
Weeks 8
8. WAP for LED blink using Raspberry Pi.
1x Breadboard
1x Raspberry Pi
1x RGB LED
1x 330Ω Resistor
2x Jumper Wires
Weeks 9:
9. Study and Implement Zigbee Protocol using Raspberry Pi.
Week 10:
10. Study and implement 6LoWPAN Border Router Implementation for IoT Devices on Raspberry
Pi.
Week 11:
11. Study and implement DTLS protocol for IoT devices using Raspberry Pi.
Week 12:
12. Study and implement CoAP protocol for IoT devices using Raspberry Pi.
Week 13:
13. Study and implement RPL protocol for IoT devices using Raspberry Pi.
Week 14
14. Study and implement MQTT protocol for IoT devices using Raspberry Pi.
Week 15:
15. Study and implement AMQP protocol for IoT devices using Raspberry Pi.
TECHNICAL ELECTIVES
Credits
L T P C
CSE 320 Web Programming TE 3 0 0 3
UNIT I
Introduction to internet-Introduction to World Wide Web (WWW)-Web browsers-Web servers-
Uniform Resource Locator (URL)- Introduction to Hyper Text Markup Language (HTML)-Standard
HTML document structure-Text and Paragraph formatting- Lists in HTML-Handling of images in web
pages-Hyperlinks- -Tables-Iframes in HTML-Forms in HTML-HTML Graphics-HTML Media
UNIT II
Introduction to Cascading Style Sheets (CSS)-CSS versions-The specification of CSS-Applying style
to a document-Media types-Document structure and CSS inheritance-Selectors in CSS-Major themes
of CSS-Style inclusion methods-CSS strings and keywords-CSS color values-Background attachment-
border in CSS-Counter in CSS-Basics of Web fonts-CSS animations- CSS tool tips-CSS Image
reflections-CSS grid container.
UNIT III
Overview of JavaScript-General syntactic characteristics of JavaScript-Primitives, Operations and
Expressions-Control statements-Arrays-Functions-Constructors-Pattern matching using regular
expressions-Error handling in JavaScript-Events and event handling-Document Object Model (DOM)-
Dynamic documents with JavaScript-Positioning elements-moving elements-Changing colors and
font-Dynamic content management-stacking elements-Locating mouse curser and Reacting to mouse
click-Dragging and dropping elements.
UNIT IV
Introduction to Hypertext Preprocessor (PHP)-General syntactic characteristics-Primitives, operations
and expressions-Control statements-Arrays-Functions-Pattern matching in PHP-Form handling-
Cookies and Session tracking-MySQL connectivity and various database operations with PHP
UNIT V
Introduction to Ajax-Ajax technology-Implementing Ajax-Applications-Ajax request-Ajax response-
Ajax XML-Introduction to JSON-JSON syntax-JSON data types-JSON arrays-Introduction to Web
APIs- Types of Web APIs-Examples of web APIs.
TEXTBOOKS
1. Thomas A. Powell, The Complete Reference HTML & CSS, Mc Graw Hill Publishers, Fifth
Edition, 2017
2. Robert W. Sebesta, Programming the World Wide Web, Pearson Publishers, Eighth Edition,
2014.
REFERENCES
1. Richard Blum, PHP, MySQL & JavaScript All-in-one, Wiley, 2018
Credits
L T P C
CSE 321 Human Computer Interaction TE 3 0 0 3
UNIT I: FOUNDATIONS OF HCI

The Human: I/O channels – Memory – Reasoning and problem solving - The computer: Devices –
Memory – Processing and networks - Interaction: Models – frameworks – Ergonomics – styles –
elements – Interactivity- Paradigms.
UNIT II: DESIGN AND SOFTWARE PROCESS

Interactive design basics – Process – Scenarios – Navigation – Screen design – Iteration and
prototyping - HCI in software process – Software life cycle – Usability engineering – Prototyping in
practice – design rationale. Design rules – principles, standards, guidelines, rules. Evaluation
Techniques – Universal Design.
UNIT III: MODELS AND THEORIES

Cognitive models –Socio-Organizational issues and stake holder requirements –Communication and
collaboration Models-Hypertext, Multimedia and WWW.
UNIT IV: MOBILE HCI

Mobile Ecosystem: Platforms, Application frameworks- Types of Mobile Applications: Widgets,
Applications, Games- Mobile Information Architecture, Mobile 2.0, Mobile Design: Elements of
Mobile Design, Tools.
UNIT V: WEB INTERFACE DESIGN

Designing Web Interfaces – Drag and Drop, Direct Selection, Contextual Tools, Overlays, Inlays and
Virtual Pages, Process Flow. Case Studies.
TEXTBOOKS
1. Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale, “Human Computer Interaction”,
Pearson Education.
2. Brian Fling, “Mobile Design and Development”, O’Reilly Media Inc. Bill Scott and
Theresa Neil, “Designing Web Interfaces”, O’Reilly.
Credits
CSE 322 Advanced Computer Architecture TE 3 0 0 3
UNIT I: INSTRUCTION LEVEL PARALLELISM

ILP – Concepts and challenges – Hardware and software approaches – Dynamic
scheduling – Speculation - Compiler techniques for exposing ILP – Branch prediction.
UNIT II: MULTIPLE ISSUE PROCESSORS

VLIW & EPIC – Advanced compiler support – Hardware support for exposing parallelism– Hardware
versus software speculation mechanisms – IA 64 and Itanium processors–Limits on ILP.
UNIT III: MULTIPROCESSORS AND THREAD LEVEL PARALLELISM

Symmetric and distributed shared memory architectures – Performance issues –
Synchronization – Models of memory consistency – Introduction to Multithreading.
UNIT IV: MEMORY AND I/O

Cache performance – Reducing cache miss penalty and miss rate – Reducing hit time –
Main memory and performance – Memory technology. Types of storage devices –
Buses – RAID – Reliability, availability and dependability – I/O performance measures –
Designing an I/O system.
UNIT V: MULTI-CORE ARCHITECTURES

Software and hardware multithreading – SMT and CMP architectures – Design issues –
Case studies – Intel Multi-core architecture – SUN CMP architecture - heterogeneous
multi-core processors – case study: IBM Cell Processor.
TEXTBOOKS
1. John L. Hennessey and David A. Patterson, “Computer architecture – A quantitative
approach”, Morgan Kaufmann / Elsevier Publishers, 4th. edition, 2007.
REFERENCES
1. David E. Culler, Jaswinder Pal Singh, “Parallel computing architecture: A
hardware/software approach”, Morgan Kaufmann /Elsevier Publishers, 1999.
2. Kai Hwang and Zhi.Wei Xu, “Scalable Parallel Computing”, Tata McGraw Hill, New
Delhi, 200
Credits
L T P C
CSE 323 Natural Language Processing TE 3 0 0 3
Natural Language Processing tasks in syntax, semantics, and pragmatics – Issues – Applications – The
role of machine learning – Probability Basics –Information theory – Collocations -N-gram Language
Models – Estimating parameters and smoothing – Evaluating language models.
UNIT II: WORD LEVEL AND SYNTACTIC ANALYSIS

Word Level Analysis: Regular Expressions-Finite-State Automata-Morphological Parsing-Spelling
Error Detection and Correction-Words and Word Classes-Part-of Speech Tagging. Syntactic Analysis:
Context-free Grammar-Constituency- Parsing-Probabilistic Parsing.
UNIT III: SEMANTIC ANALYSIS AND DISCOURSE PROCESSING

Semantic Analysis: Meaning Representation-Lexical Semantics- Ambiguity-Word Sense
Disambiguation. Discourse Processing: Cohesion-Reference Resolution- Discourse Coherence
and Structure.
UNIT IV: NATURAL LANGUAGE GENERATION AND MACHINE TRANSLATION

Natural Language Generation: Architecture of NLG Systems- Generation Tasks and
Representations- Application of NLG. Machine Translation: Problems in Machine Translation-
Characteristics of Indian Languages- Machine Translation Approaches-Translation involving Indian
Languages.
UNIT V: INFORMATION RETRIEVAL AND LEXICAL RESOURCES

Information Retrieval: Design features of Information Retrieval Systems-Classical, Non-classical,
Alternative Models of Information Retrieval – valuation Lexical Resources: WorldNet-Frame Net-
Stemmers-POS Tagger- Research Corpora.
TEXTBOOKS
1. Daniel Jurafsky, James H. Martin, “Speech & language processing”, Pearson publications.
2. James Allen, Natural Language Understanding. The Benajmins/Cummings Publishing
Company Inc. 1994. ISBN 0-8053-0334-0
3. Bird, Steven, Ewan Klein, and Edward Loper, Natural language processing with Python:
Analyzing text with the natural language toolkit, O'Reilly Media, Inc, 2009.
4. Manning, Christopher, and Hinrich Schutze. Foundations of statistical natural language
processing. MIT press, 1999.
REFERENCES
1. Pierre M. Nugues, “An Introduction to Language Processing with Perl and Prolog”, Springer.
2. Cover, T. M. and J. A. Thomas, Elements of Information Theory, Wiley, 1991. ISBN 0-471-
06259-6.
3. Charniak, E.: Statistical Language Learning. The MIT Press. 1996. ISBN 0-262-53141-0.
4. Tom Mitchell, Machine Learning. McGraw Hill, 1997. ISBN 0070428077.
Credits
L T P C
CSE 324 Computer Graphics TE 3 0 0 3
Application areas of Computer Graphics, overview of graphics systems, video-display devices, raster-
scan systems, random scan systems, graphics monitors, and workstations and input devices
Output primitives: Points and lines, line drawing algorithms, mid-point circle and ellipse algorithms.
Filled area primitives: Scan line polygon fill algorithm, boundary-fill, and flood-fill algorithms.
UNIT II: 2-D GEOMETRICAL TRANSFORMS

Translation, scaling, rotation, reflection and shear transformations, matrix representations and
homogeneous coordinates, composite transforms, transformations between coordinate systems.
2-D Viewing: The viewing pipeline, viewing coordinate reference frame, window to view-port
coordinate transformation, viewing functions, Cohen-Sutherland and Cyrus-beck line clipping
algorithms, Sutherland –Hodgeman polygon clipping algorithm.
UNIT III: 3-D OBJECT REPRESENTATION

Polygon surfaces, quadric surfaces, spline representation, Hermite curve, Bezier curve and B-spline
curves, Bezier and B-spline surfaces. Basic illumination models, polygon rendering methods.
3-D Geometric transformations: Translation, rotation, scaling, reflection and shear transformations,
composite transformations, 3-D viewing: Viewing pipeline, viewing coordinates, view volume and
general projection transforms and clipping.
UNIT IV: VISIBLE SURFACE DETECTION METHODS

Classification, back-face detection, depth-buffer, scan-line, depth sorting, BSP-tree methods, area sub-
division and octree methods.
UNIT V: COMPUTER ANIMATION

Design of animation sequence, general computer animation functions, raster animation, computer
animation languages, key frame systems, motion specifications
TEXTBOOKS
1. Computer Graphics with Virtual Reality System, Rajesh K. Maurya, Wiley Dreamtech.
2. Computer Graphics, D. Hearn and M.P. Baker (C Version), Pearson Education
REFERENCES
1. Computer Graphics Principle and Practice, J.D. Foley, A.Dam, S.K. Feiner, Addison, Wesley
2. “Procedural elements for Computer Graphics”, David F Rogers, Tata Mc Graw hill, 2nd
edition.
3. “Principles of Interactive Computer Graphics”, Neuman and Sproul, TMH.
4. Principles of Computer Graphics”, Shalini, Govil-Pai, Springer.
Credits
L T P C
CSE 325 Advanced Data Structures and Algorithms TE 3 0 0 3
UNIT I: ADVANCED DATA STRUCTURES

Strategies for choosing the appropriate data structures-Heaps, AVL Trees (Search, Insertion, Deletion,
Red-Black Trees (Search, Insertion and Deletion), Splay Trees (Search, Insertion and Deletion), B-
trees, B+ Trees (Search, Insertion and Deletion), Fibonacci heaps, Data Structures for Disjoint Sets,
Augmented Data Structures.
UNIT II: GRAPHS & ALGORITHMS

Cut-sets, Connectivity and Separability, Planar Graphs, Isomorphism, Graph Coloring, Covering and
Partitioning, Topological sort, Max flow: Ford Fulkerson algorithm, max flow – min cut, Dynamic
Graphs, Few Algorithms for Dynamic Graphs, Union-Find Algorithms.
UNIT III: GEOMETRIC ALGORITHMS

Point location, Convex hulls and Voronoi diagrams, Arrangements, graph connectivity, Network
Flow and Matching: Flow Algorithms - Maximum Flow – Cuts - Maximum Bipartite Matching - Graph
partitioning via multi-commodity flow, Karger'r Min Cut Algorithm, String matching and document
processing algorithms.
UNIT IV: APPROXIMATION ALGORITHMS

Approximation algorithms for known NP hard problems - Analysis of Approximation Algorithms. Use
of Linear programming and primal dual, Local search heuristics. Parallel algorithms: Basic techniques
for sorting, searching, merging, list ranking in PRAMs and Interconnection.
UNIT V: RANDOMIZED ALGORITHMS

Introduction, Type of Randomized Algorithms, Min- Cut, 2-SAT, Game Theoretic Techniques,
Random Walks. Online Algorithms: Introduction, Online Paging Problem, Adversary Models, k-
server Problem
TEXTBOOKS
1. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, “Introduction
to Algorithms”, Third Edition, The MIT Press, 2009.
REFERENCES
1. Sahni, Sartaj, Data Structures, Algorithms and Applications in C++, MIT Press (2005)
2. Roger Sedgewick and Kevin Wayne, Algorithms, Addison-Wesley Professional 2011.
3. Allan Borodin and Ran El-Yaniv: Online Computation and Competitive Analysis, Cambridge
University Press, 2005.
4. Sanjoy Dasgupta, Christos Papadimitriou and Umesh Vazirani, “Algorithms”, Tata McGraw-
Hill, 2009.
5. RK Ahuja, TL Magnanti and JB Orlin, “Network flows: Theory, Algorithms, and
Applications”, Prentice Hall Englewood Cliffs, NJ 1993.
6. Rajeev Motwani, Prabhakar Raghavan: Randomized Algorithms, Cambridge University Press,
1995.
7. Jiri Matousek and Bernd Gärtner: Understanding and Using Linear Programming, 2006.
Credits
L T P C
CSE 326 Distributed Operating Systems TE 3 0 0 3
UNIT I: FUNDAMENTALS
What is distributed operating system, issues in designing distributed operating system, Computer
networks: Lan, WAN technologies, communication protocols, internetworking, Message passing:
Issues in IPC by message passing, synchronization, buffering group communication, case study.
UNIT II: REMOTE PROCEDURE CALLS

The RPC model, Implementing RPC, RPCs in heterogeneous environment, lightweight RPC, case
study. Distributed shared memory: General architecture of DSM systems, Design and implementation
issues of DSM, Consistency models, Replacement strategies, Advantages of DSM.
UNIT III: PROCESS MANAGEMENT

Introduction, Process migration, Threads. Synchronization: Clock synchronization, event ordering,
Mutual exclusion, deadlock, Election Algorithms. Resource management: Global scheduling
algorithm, Task assignment, Load sharing and balancing approaches.
UNIT IV: DISTRIBUTED FILE SYSTEM

Desirable features of a good DFS, file models, file accessing models, file sharing semantics, file
caching schemes, file replication, fault tolerance, atomic transactions, Design principles, Case
study: Google DFS and Hadoop DFS.
UNIT V: NAMING
Desirable features of a good naming system, system-oriented Names, object locating mechanisms,
human oriented Names, Name caches, naming and security. Security: potential attacks, cryptography,
authentication, access control, digital signatures, design principles.
1. Pradeep K Sinha, “Distributed Operating Systems: Concepts and Design”, Prentice Hall of
India, 2007.
2. Advanced Concepts in Operating Systems, Mukesh Singhal and Niranjan Shivratri, Mc Graw
hill publications, 2017
Pearson publications, 2nd edition.
Credits
L T P C
CSE 420 Data and Web Mining TE 3 0 0 3
UNIT I: INTRODUCTION TO DATA MINING

What is data mining? Related technologies - Machine Learning, DBMS, OLAP, Statistics. Data
Mining Goals. Stages of the Data Mining Process, Data Mining Techniques, Knowledge
Representation Methods. Data Warehouse and OLAP: Data Warehouse and DBMS, Multidimensional
data model, OLAP operations .
UNIT II: DATA PRE-PROCESSING

Data cleaning. Data transformation, Data reduction. Data mining knowledge representation, Attribute-
oriented analysis. Data mining algorithms: Association rules: Motivation and terminology, Basic idea:
item sets, generating item sets and rules efficiently, Correlation analysis.
UNIT III: DATA MINING ALGORITHMS

Classification, Basic learning/mining tasks, inferring rudimentary rules: 1R algorithm, Decision trees,
Covering rules. Data mining algorithms: Prediction, The prediction task, Statistical (Bayesian)
classification, Bayesian networks, Instance-based methods (nearest neighbour), Linear models.
UNIT IV: WEB CRAWLING

Basic crawler algorithm, Focused crawlers, Topical crawlers, Web search: Web page pre-processing,
Inverted index, HITS algorithm, Page ranking algorithm, Leadership algorithm.
UNIT V: SOCIAL NETWORK ANALYSIS

Co-citation and bibliographic coupling, Community discovery. Web usage mining: Recommender
systems. Mining Twitter, Mining Face book, Mining Instagram.
1. Han, J., Kamber, M., & Pei, J. (2011). Data mining: Concepts and techniques (3rd ed.). Morgan
Kaufmann publications.
2. Introduction to Data Mining, Vipin kumar, Michael Steinbach, Pang-Ning Tan, Person
publications,2016
3. Mining the Web, Soumen Chakrabarti, Elseier publications, 2002
4. Web Data Mining, Bing Liu, Second Edition, Springer publications, 2011.
5. Mining the Social Web, Mathew A. Russel, Mikhail Klassen, Third edition, Oreily
publications, 2018.
Credits
L T P C
CSE 421 Complexity Theory TE 3 0 0 3
UNIT I: COMPUTABILITY
A recap of automata theory and the Church-Turing Thesis Computational models: Lambda calculus,
Turing machine Decidability Reducibility. The PCP problem & Mapping reducibility The Recursion
Theorem Definition of Information.
UNIT II: TIME COMPLEXITY

Measuring Complexity, Big-O and small-o notation, Analyzing algorithms. Complexity relationships
among computational models The Class-P, Examples The Class-NP, Examples The P versus NP
question NP-completeness The Cook-Levin Theorem Additional NP-completeness Problems.
UNIT III: SPACE COMPLEXITY

Space complexity. Savitch's Theorem and NL. NL-completeness and log-space reductions. From P-
completeness to PSPACE-completeness. The Classes L and NL NL completeness, NL equals coNL.
UNIT IV: INTERACTABILITY

Hierarchy Theorems Relativization Circuit Complexity.
UNIT V: ADVANCED TOPICS IN COMPLEXITY THEORY

Approximation Algorithms Probabilistic Algorithms Alternation Interactive Proof Systems.
TEXTBOOKS
1. Introduction to the Theory of Computation - Michael Sipser (Primary Textbook)
2. Computational Complexity - Arora Barak (Reference)
Credits
L T P C
CSE 422 Software Project Management TE 3 0 0 3
UNIT I: SOFTWARE MANAGEMENT & ECONOMICS

SDLC -waterfall model Conventional Software Management Performance Evolution of Software
Economics – Software economics Pragmatic software cost estimation Reducing software product size
Improving software processes Improving team effectiveness Improving automation through software
environment.
UNIT II: THE OLD AND THE NEW WAY OF PROJECT MANAGEMENT
The principles of conventional software engineering Principles of modern software management,
Transitioning to an iterative process Basics of Software estimation – Effort and Cost estimation
techniques COSMIC Full function points COCOMO-I COCOMO II A Parametric Productivity Model
- Staffing Pattern.
UNIT III: SOFTWARE MANAGEMENT PROCESS FRAMEWORK

Life cycle phases: Engineering and production stages, inception, Elaboration, construction, transition
phases. Artifacts of the process: The artifact sets, Management artifacts, Engineering artifacts,
programmatic artifacts Model based software architectures: A Management perspective. Model based
software architectures: Technical perspective Work Flows of the process: Software process workflows
Iteration workflows Checkpoints of the process: Major milestones, Minor Milestones, Periodic status
assessment.
UNIT IV: PROJECT ORGANIZATION AND PLANNING

Work breakdown structures Planning guidelines. The cost and schedule estimating process The
iteration planning process Pragmatic planning Line-of-Business organizations Project organizations,
Evolution of organizations Process automation - Automation building Blocks The project
environment.
UNIT V: PROJECT CONTROL AND PROCESS INSTRUMENTATION

The Seven-Core metrics: Management indicators The Seven-Core metrics: Quality indicators Life-
Cycle expectations, Pragmatic software metrics, Metrics automation Modern project profiles Next
generation software economics Modern process transitions.
TEXBOOKS/REFERENCES
1. Walker Royce, “Software Project Management”, 1st Edition, Pearson Education, 2006.
2. Bob huges, Mike cotterell, Rajib Mall “Software Project Management”, 6th Edition, Tata
McGraw Hill, 2017.
3. SA Kelkar, Software Project Management: A Concise Study, 3rd Edition, PHI, 2013.
4. Joel Henry, Software Project Management: A Real-World Guide to Success, Pearson
Education, 2009.
5. Pankaj Jalote, Software Project Management in Practice, Pearson Education, 2015.
6. https://ocw.mit.edu/courses/engineering-systems-division/esd-36-system-project-
management-fall-2012/
7. https://uit.stanford.edu/pmo/pm-life-cycle
Credits
L T P C
CSE 423 Multimedia TE 3 0 0 3
UNIT I: INTRODUCTION TO MULTIMEDIA

What is Multimedia, Multimedia and Hypermedia, Overview ofMu1timedia Software Tools Graphics
and Multimedia Data Representations: Graphics Image Data Types, File Formats, and representation
(image, video, and sound).
UNIT II: COLOUR IN IMAGE AND VIDEO

Color Science, Color' Models in Images, Color Models in Video, Fundamental Concepts in Video,
Analog Video, Digital Video Basics of Digital Audio: Digitization of Sound, MIDI: Musical
Instrument Digital Interface Quantization and Transmission of Audi.
UNIT III: LOSSLESS COMPRESSION ALGORITHMS

Basics of Infonnation Theory, Run-Length Coding, Variable-Length Coding, Dictionary-Based
Coding, Arithmetic Coding, Lossless Image Compression Lossy Compression Algorithms:
Distortion Measures, The Rate-Distortion Theory Quantization, Transform Coding, Wavelet-Based
Coding, Embedded Zerotree of Wavelet Coefficients.
UNIT IV: IMAGE COMPL'ESSION STANDARDS

The JPEG Standard, The JPEG2000 Standard, The JPEG-LS Standard, Bilevel Image Compression
Standards.
Basic Video Compression Techniques: Introduction to Video Compression, Video Compression
Based on Motion Compensation, Search for Motion Vectors, H.261, H.263.
Basic Audio Compression Techniques: ADPCM in Speech Coding, G.726 ADPCM, Vocoders.
UNIT V: MPEG Video Coding I - MPEG-1 and 2

MPEG-1, MPEG-2 MPEG Video Coding 11- MPEG-4, 7, and Beyond: Overview ofMPEG-4,
Object-Based Visual Coding in MPEG-4, Synthetic Object Coding in MPEG-4, MPEG-4
Part10/H.264, MPEG-7, H.265 MPEG Audio Compl'ession: MPEG Audio, Commercial Audio
codes.
TEXTBOOKS
1. Fundamentals of Multimedia (FM), Ze-Nian Li, Mark S. Drew, in Prentice Hall,
2004 (Springer 2nd Edition, 2014 with additional author of Dr. Jiangchuan Liu).
2. Digital Multimedia by Chapman (DM), Nigel P./ Chapman, Jenny, in John Wiley & Sons
Inc, 2000 (3rd Edition, 2009).
REFERENCES
1. Multimedia: Making It Work, 9 Edition by Vaughan, Tay in McGraw-Hill, 2014.
2. Multimedia: Computing, Communications and Applications by Ralf Steinmetz in Pearson
Education, 2012.
3. Recent articles about multimedia (recommended at classes).
Credits
L T P C
CSE 424 Deep Learning TE 3 0 0 3
Overview of machine learning, linear classifiers, loss functions.
Introduction to Tensor Flow: Computational Graph, Key highlights, creating a Graph, Regression
example, Gradient Descent, Tensor Board, Modularity, Sharing Variables, Keras.
UNIT II: Activation Functions

Sigmoid, ReLU, Hyperbolic Fns, Softmax Perceptrons: What is a Perceptron, XOR Gate.
Artificial Neural Networks: Introduction, Perceptron Training Rule, Gradient Descent Rule, vanishing
gradient problem and solution.
UNIT-III: Convolutional Neural Networks

Introduction to CNNs, Kernel filter, Principles behind CNNs, Multiple Filters, problem, and solution
of under fitting and over fitting.
UNIT IV: Recurrent Neural Networks

Introduction to RNNs, Unfolded RNNs, Seq2Seq RNNs, LSTM, GRU, Encoder Decoder
architectures.
UNIT V: Deep Learning applications

Image segmentation, Self-Driving Cars, News Aggregation and Fraud News Detection Natural
Language Processing, Virtual Assistants, Entertainment, Visual Recognition Fraud Detection,
Healthcare.
TEXTBOOKS
1. Goodfellow, I., Bengio, Y., and Courville, A., Deep Learning, MIT Press, 2016.
2. Josh Patterson, Adam Gibson, Deep Learning: A Practitioner's Approach, OReilly, 2017.
3. Gulli, Antonio, and Sujit Pal. Deep learning with Keras. Packt Publishing Ltd, 2017.
4. Buduma, Nikhil, and Nicholas Locascio. Fundamentals of deep learning: Designing next-
generation machine intelligence algorithms. " O'Reilly Media, Inc.", 2017.
REFERENCES
1. Bishop, C., M., Pattern Recognition and Machine Learning, Springer, 2006.
2. Yegnanarayana, B., Artificial Neural Networks PHI Learning Pvt. Ltd, 2009.
3. Golub, G., H., and Van Loan, C. F., Matrix Computations, JHU Press,2013.
4. Satish Kumar, Neural Networks: A Classroom Approach, Tata McGraw-Hill Education, 2004.
Credits
CSE 425 Advanced Database Management Systems TE 3 0 0 3
UNIT I
Overview of the DBMS Introduction to DBMS implementation using Megatron 2000 database system
Data storage using main memory and hard disks Disk failures Recovery from disk crashes
Representing data elements: Record, Representing block and record address Variable length data and
records Record modifications.
UNIT II
Index structures: Indexes on sequential files Secondary indexes B-Trees Hash tables Multidimensional
indexes: Hash and tree like structures for multidimensional data Bitmap indexes.
UNIT III
Query execution: Algebra for queries Introduction to Physical-Query-Plan Operators One-Pass
Algorithms for Database Operations Nested-Loop Joins Two-Pass Algorithms Based on Sorting Two-
Pass Algorithms Based on Hashing Index-Based Algorithms Buffer Management Algorithms Using
More Than Two Passes Parallel Algorithms for Relational Operations.
UNIT IV
The query compiler: Parsing Algebraic Laws for Improving Query Plans from Parse Trees to Logical
Query Plans Estimating the Cost of Operations Introduction to Cost-Based Plan Selection Choosing
an Order for Joins Completing the Physical-Query-Plan Selection.
UNIT V
Concurrency control: Conflict-Serializability View serializability Enforcing Serializability by Locks
Locking Systems with Several Lock Modes. An Architecture for a Locking Scheduler Concurrency
control by timestamps and validation Transactions that Read Uncommitted Data Coping with system
failures: Undo/Redo logging Protecting media failures
TEXTBOOKS
1. R. Ramakrishnan, J. Gehrke, Database Management Systems, McGraw Hill, 2004.
2. A. Silberschatz, H. Korth, S. Sudarshan, Database system concepts, 5/e, McGraw Hill, 2008.
REFERENCES
1. K. V. Iyer, Lecture notes available as PDF file for classroom use.
Credits
L T P C
CSE 426 Fog Computing TE 3 0 0 3
UNIT I: FOG COMPUTING

Limitation of Cloud computing, Differences between Cloud and Fog computing, what is Fog?
Advantages of Fog computing, Business Models, Architecture of Fog computing, Opportunities and
Challenges.
UNIT II: ADDRESSING THE CHALLENGES IN FOG RESOURCES

Introduction, Taxonomy and Characteristics, Resource Management Challenge, Optimisation
challenges, Miscellaneous Challenges, IoT and Fog: Introduction. Programming paradigms for IoT+
Fog, Research challenges and Future Research Directions.
UNIT III: MANAGEMENT AND ORCHESTRATION OF NETWORK

SLICES IN 5G, FOG, EDGE, AND CLOUDS
Introduction, Background, Network Slicing in 5G, Network Slicing in Software-Defined Clouds,
Network Slicing Management in Edge and Fog, Future Research Directions: Middleware for Fog and
Edge Computing: Design Issues, Introduction. Need for Fog and Edge Computing Middleware: Design
Goals, State-of-the-Art Middleware Infrastructures, System Model, Clusters for Lightweight Edge
Clouds, Architecture Management – Storage and Orchestration, IoT Integration, Security Management
for Edge Cloud Architectures, Future Research Directions.
UNIT IV: DATA MANAGEMENT AND ANALYSIS IN FOG COMPUTING

Introduction, Background, Fog Data Management, Future Research and Direction Motivating
Example: Smart Building, Predictive Analysis with Fog Torch, Survey of ML Techniques for
Defending IoT Devices, Machine Learning in Fog Computing, Future Research Directions.
UNIT V: CASE STUDIES

Case Study 1: Introduction, Human Object Detection, Object Tracking, Lightweight Human Detection.
Case Study 2: Introduction, Data-Driven Intelligent Transportation Systems, Mission-Critical
Computing Requirements of Smart Transportation Applications, Fog Computing for Smart
Transportation Applications, Case Study 3: Intelligent Traffic Lights Management (ITLM) System,
Testing Perspectives.
TEXTBOOKS
1. Fog and Edge Computing, Rajkumar Buyya, Satish Narayana Srirama, Wiley Publications,
2019.
2. Fog computing in the Internet of Things: Springer publications, 2018
REFERENCES
1. Research papers from IEEE, ACM, Springer and Elsevier)
Credits
L T P C
CSE 427 Parallel Algorithms TE 3 0 0 3
UNIT I
Sequential model need of alternative model, parallel computational 8 models such as PRAM, LMCC,
Hypercube, Cube Connected Cycle, Butterfly, Perfect Shuffle Computers, Tree model, Pyramid
model, Fully Connected model, PRAM-CREW, EREW models, simulation of one model from another
one.
UNIT II
Performance Measures of Parallel Algorithms, speed-up and 8 efficiency of PA, Cost- optimality, an
example of illustrate Cost- optimal algorithms- such as summation, Min/Max on various models.
UNIT III
Parallel Sorting Networks, Parallel Merging Algorithms on on 8 CREW/EREW/MCC, Parallel Sorting
Networks CREW/EREW/MCC/, linear array.
UNIT IV
Parallel Searching Algorithm, Kth element, Kth element in X+Y on 8 PRAM, Parallel Matrix
Transportation and Multiplication Algorithm on PRAM, MCC, Vector-Matrix Multiplication, Solution
of Linear Equation, Root finding.
UNIT V
Graph Algorithms - Connected Graphs, search and traversal, 8 Combinatorial Algorithms-
Permutation, Combinations, Derangements.
TEXTBOOKS
1. M.J. Quinn, “Designing Efficient Algorithms for Parallel Computer”, Mc Graw Hill.
2. S.G. Akl, “Design and Analysis of Parallel Algorithms” 3. S.G. Akl,” Parallel Sorting
Algorithm” by Academic Press.
Credits
L T P C
CSE 428 Web Services TE 3 0 0 3
UNIT-I
Introduction to Service Oriented Architecture-Goals of service oriented architecture- Introduction to
services-The SOA Architectural Stack-Service Composition and Data Flow-Data-Flow Paradigms-
Composition Techniques
UNIT-II
Introduction to web services- History of webservices-Web services: communication stack-Simple
Object Access Protocol (SOAP)-Web Services Description Language (WSDL)-WSDL Main
Elements-Message Communication Model in SOAP/WSDL
UNIT-III
Web Services: REST or Restful Services-REST Design Principles-Web API Design for RESTful
Services-Data Services-Implementation of Data Services-XML Transformation and Query
Techniques-Consuming data via direct data access to the sources
UNIT-IV
Web Service Composition: Overview-Service Orchestration vs. Service Choreography-Benefits of
Web Service Composition-Web Service Composition Environment-Web Service Composition:
Control Flows-BPEL (Business Process Execution Language)-BPMN (Business Process Model and
Notation)-Web Service Composition: Data Flows-Data-Flow Paradigms
UNIT-V
Introduction to Service Component Architecture (SCA)-The SOA Integration Problem-Overview of
SCA-High-level overview of the assembly model-Application of SCA to Use Case-SCA Runtime-
Benefits of SCA
TEXTBOOKS
1. Paik, Hye-young, et al. Web Service Implementation and Composition Techniques. Vol. 256.
Springer International Publishing, 2017.
2. Martin Kalin, Java Web Services: Up and Running, O’Reilly publishers, Second edition, 2013.
Credits
L T P C
CSE 429 Advances in Data Mining TE 3 0 0 3
UNIT I
What is Data Mining, Compiling need of Data Mining, Business Data Mining, Data Mining Tools.
Data Mining Process, CRISP-DM, Business Understanding, Data Understanding, Data Preparation,
Modelling, Evaluation, Deployment. SEMMA, Steps in SEMMA Process, Comparison of CRISP &
SEMMA, Handling Data.
UNIT II
Association Rules in Knowledge Discovery, Market-Basket Analysis, Mining Frequent Patterns,
Associations, and Correlations, Apriori Algorithm, Pattern-Growth Approach for Mining Frequent
Itemsets, Mining Frequent Itemsets using Vertical Data Format, Mining Closed and Max Patterns.
Pattern Mining in Multilevel, Multidimensional Space, Constraint-Based Frequent Pattern Mining,
Mining High-Dimensional Data and Colossal Patterns, Mining Compressed or Approximate Patterns.
UNIT III
Classification: Basic Concepts, Decision Tree Induction, Bayes Classification Methods: Bayes’
Theorem, Na¨ıve Bayesian Classification, Rule-Based Classification. Model Evaluation and Selection,
Techniques to Improve Classification Accuracy: Bagging, Boosting and AdaBoost, Random Forests,
Improving Classification Accuracy of Class-Imbalanced Data. Other Classification Methods: Genetic
Algorithms, Rough Set Approach, Fuzzy Set Approaches.
UNIT IV
Cluster Analysis, Partitioning Methods: k-Means: A Centroid-Based Technique, k-Medoids: A
Representative Object-Based Technique. Hierarchical Methods: Agglomerative versus Divisive
Hierarchical Clustering, Distance Measures in Algorithmic Methods, BIRCH: Multiphase Hierarchical
Clustering Using Clustering, Feature Trees, Chameleon: Multiphase Hierarchical Clustering Using
Dynamic Modelling, Probabilistic Hierarchical Clustering. Density-Based Methods, Grid-Based
Methods.
UNIT V
Outliers and Outlier Analysis, Outlier Detection Methods: Supervised, Semi-Supervised, and
Unsupervised Methods, Statistical Methods, Proximity-Based Methods, and Clustering-Based
Methods, Mining Contextual and Collective Outliers, Outlier Detection in High-Dimensional Data.
Mining Complex Data Types, Data Mining Applications, Social Impacts of Data Mining.
TEXTBOOKS
1. Data Mining Concepts and Techniques, Third Edition, by Jiawei Han, Micheline Kamber, and
Jian Pei.
2. Olson DL, Delen D. Advanced data mining techniques. Springer Science & Business Media.
REFERENCES
1. Aggarwal CC. Data mining: the textbook. Springer. William
2. Machine Learning, 2nd edition, by Ethem Alpaydi

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School of Engineering and Applied Sciences

B. Tech Computer Science and Engineering

Academic Batch: 2021-2025

Department of Computer Science Engineering

List of Technical Electives

UNIT I: DERIVTIVES AND DIFFERENTITATION

UNIT II: APPROXIMATIONS AND THEIR APPLICATIONS

UNIT III: THE INTEGRAL AND INTEGRATION THEORY

UNIT IV: DIFFERENT INTEGRATION TECHNIQUES AND

UNIT V: POLAR CO-ORDINATE SYSTEMS AND INFINITE SERIES

UNIT I: INTRODUCTION TO VECTOR ALGEBRA

UNIT II: ELECTROSTATICS

UNIT III: DIELECTRICS AND POLARIZATION

UNIT IV: MAGNETOSTATICS

UNIT V: INTRODUCTION TO ELECTRODYNAMICS

LIST OF PRACTICAL EXPERIMENTS

UNIT I: BASIS OF LIFE AND DIVERSITY

UNIT II: CELL BIOLOGY

UNIT III: MOLECULAR BIOLOGY

UNIT IV: ENZYMES AND APPLICATIONS

UNIT V: BIOLOGICAL SEQUENCES AND DATABASES

UNIT III: MODULAR PROGRAMMING

UNIT IV: POINTERS

UNIT V: ENUMERATED, STRUCTURE AND UNION TYPES

LIST OR PRACTICAL EXPERIMENTS

6. Week-7: Functions and array

7. Weak-8: Pre-processor directives

9. Weak-10: String operations without using the built-in functions

10. Weak-11: Pointers

11. Weak-12: Pointers and array

12. Weak-13: Recursion

13. Weak-14: File Operations

14. Weak-15: Command line arguments

UNIT II: REASONING

UNIT III: VERBAL

UNIT IV: COMMUNICATION SKILLS

TEXTBOOKS/REFERENCE BOOKS/OTHER READING MATERIAL

UNIT I: VECTOR AND MATRICES

UNIT II: PARTIAL DERIVATIVES

UNIT III: DOUBLE INTEGRAL AND LINE INTEGRALS IN THE PLANE

UNIT IV: TRIPLE INTEGRALS IN 3D

UNIT V: SURFACE INTEGRAL IN 3D

UNIT I: ELECTRICAL QUANTITIES AND THEIR MEASUREMENT

UNIT II: SEMICONDUCTOR DEVICES

UNIT III: A.C. CIRCUITS AND OPERATIONAL AMPLIFIER

UNIT IV: ELECTRONIC FILTERS

UNIT V: DIGITAL LOGIC FUNDAMENTALS

LIST OF PRACTICAL EXPERIMENTS

UNIT III: TREES

UNIT IV: GRAPHS

UNIT V: SORTING AND SEARCHING TECHNIQUES

2. “Data Structures Using C” by Aaron M. Tanenbaum, Yedidvah Langsam, and Moshe J.

LIST OF PRACTICAL EXPERIMENTS

1. Week 5 &6: Demonstrate the following though simulation:

Reference(s): Data Structures and Program Design in C by Robert Kruse, C L Tondo,

Reference(s): Data Structures and Program Design in C by Robert Kruse, C. L. Tondo ,

UNIT I: CHEMICAL BONDING

UNIT II: PHASE RULE, THERMOCHEMISTRY, AND KINETICS

UNIT III: CRYSTALLINE MATERIALS