MCA KTU Syallabus
MCA KTU Syallabus
MCA KTU Syallabus
SYLLABUS
For
Semester 5 and 6
SEMESTER 5
ELECTIVE-II ELECTIVE-III
RLMCA361 Compiler Construction RLMCA381 Cloud Computing
RLMCA363 IPR and Cyber Law RLMCA383 Human Computer Interaction
RLMCA365 Cyber Forensics RLMCA385 Bioinformatics
RLMCA367 Internet of Things RLMCA387 Computer Graphics
RLMCA369 Python Programming RLMCA389 Parallel and Distributed Computing
RLMCA371 Social Network Analysis RLMCA391 Artificial Intelligence
SEMESTER 6
Sessio ESE
Total Credits Exam
Regular Master of Computer Applications Hours / week nal Marks
Slot
Course No Course L T P
RLMCA352 Project and Viva Voce 30 70 30 100 12
Cumulative Total 3600 123
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA301 Web Data Mining 3-1-0-4 2016
Course Objectives
Web Data Mining - Basic Concepts of Association Rules - Supervised Learning - Unsupervised Learning -
Information Retrieval and Web Search - Web Usage Mining.
Expected Outcome
References
1. Bing Liu, “Web Data Mining - Exploring Hyperlinks, Contents and Usage Data”, Second edition,
Springer 2011.
2. Matthew A Russell, “Mining the social web: Data Mining Facebook, Twitter, LinkedIn, Google+,
GitHub and more”, Second Edition, O’Reilly October 2013.
3. Jiawei Han and Micheline Kamber, “Data Mining Concepts & Techniques”, Second Edition,
Elsevier.
4. Alex Berson and Stephen J Smith, “Data Warehousing, Data Mining & OLAP”, Tata McGraw –Hill
Edition, Tenth Reprint 2007.
5. Pang Ning Tan, Michael Steinbach and Vipin Kumar, “ Introduction To Data Mining”, Pearson
Education, 2007.
Suggested MOOC
1. https://ocw.mit.edu/courses/sloan-school-of-management/15-062-data-mining-spring-
2003/lecture-notes/
2. http://www.cs.virginia.edu/~hw5x/Course/CS6501-Text-Mining/_site/lectures/
Course Plan
A P J Abdul Kalam Technological University
MCA Regular syllabus – Semester 5 & 6
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
Introduction - World Wide Web - Web Data Mining - Data Mining - Web
Mining - Data Mining Foundations - Basic Concepts of Association Rules -
Apriori Algorithm - Data Formats for Association Rule Mining - Basic
I Concepts of Sequential Patterns - Mining Sequential Patterns based on 8 15
Generalised Sequential Pattern (GSP) Algorithm
Text : 1
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M). There
will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with an
alternative choice question from the same module (6 x 6M=36M).The maximum
number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA303 E-Commerce 3-1-0-4 2016
Course Objectives
Syllabus
Expected Outcome
References
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B
(Essay) together from a single module, not to exceed the marks assigned to
that module specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLMCA305 Cryptography and Cyber Security 3-1-0-4 2016
Course Objectives
Syllabus
Introduction to Cryptography, Security architecture and classical encryption schemes, Number theory
basics, Conventional symmetric key encryption techniques, Public key cryptography, Digital signatures,
Message Authentication codes and Hash functions, Crypto currencies and bitcoins, Cyber Security, Email
Security, IP Security and Web Security.
Expected Outcome
References
1. William Stallings, Cryptography and Network Security, 6th Edition, Pearson Education, March
2013.
2. Behrouz A. Forouzan, “Cryptography and Network Security”, Tata McGraw-Hill Publishing(2e
2011)
3. Charlie Kaufman, Radia Perlman and Mike Speciner, “Network Security”, Prentice Hall of India,
2002.
4. Manuel Mogollon, “Cryptography and Security Services – Mechanisms and Applications”,
Cybertech Publishing.
5. William R. Cheswick, Steven M. Bellovin, Aviel D. Rubin, “Firewalls and Internet Security” Addison-
Wesley
6. Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder, “Bitcoin
and Cryptocurrency technologies”, Princeton University Press
Suggested MOOC
1. https://www.coursera.org/learn/crypto
2. https://www.coursera.org/learn/cryptocurrency
3. https://www.coursera.org/learn/crypto2
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
VI 10 20%
IPSecurity: Overview of IPSec – IPv4 and IPv6-Authentication Header-
Encapsulation Security Payload (ESP)-Internet Key Exchange. Web
Security: SSL/TLS Basic Protocol-computing the keys- client
authentication-PKI as deployed by SSL Attacks fixed in v3- Exportability-
Encoding-Secure Electronic Transaction (SET).
END SEMESTER EXAM
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA361 Elective II- Compiler Construction 3-0-1-4 2016
Course Objectives
● To introduce the major concept areas of language translation and compiler design.
● To enrich the knowledge in various phases of compiler and its use, token generation, parsing,
creating intermediate codes, code optimization techniques, machine code generation, and use
of symbol table.
● To provide practical programming skills necessary for constructing a compiler.
Syllabus
Context of a lexical analyzer – construction of lexical analyzer, deterministic and non-deterministic finite
automata. Compile time error handling, error detection, reporting, recovery and repair.
Basic parsing techniques – Top down parsing – recursive descent parser, predictive parser simple LL(1)
grammar. Bottom up parsers, operator precedence parser, LR grammar, LR(0), SLR(1) parsers.
Intermediate codes, translation of assignments, translation of array reference, Boolean expressions, case
statements, back patching.
Code optimization, loop optimization and global optimization, sources of sample code generation.
Expected Outcome
At the end of the course, students will be able to
References
1. Alfred V Aho and Jeffery D Ullman , Principles of Compiler Design - Techniques and Tools, Pearson
Edn, 2nd edn, 2009
2. V Raghavan- Principles of Compiler Design – TMH, 2nd ed,2011
3. Jean Paul Tremblay and Sorenson., The Theory and Practice of Compiler Writing McGraw Hill
4. Principles of compiler design, 2nd ed, Nandini Prasad, Elsevier
5. Kenneth C.Louden, Compiler Construction-Principles and Practice, 2nd Edition, Cengage, 2010.
6. Keith Cooper and Linda Torczon, “Engineering a Compiler”, 2nd Edition, Elsevier, 2011
7. Principles of Compiler, A new approach to Compilers including the algebraic methods, Su, Yunlin,
Yan, Song Y., SPRINGER
Suggested MOOC
1. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-035-computer-
language-engineering-spring-2010/lecture-notes/
2. http://nptel.ac.in/courses/106108113/
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B
(Essay) together from a single module, not to exceed the marks assigned to
that module specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA363 Elective II- IPR and Cyber Law 3-0-1-4 2016
Course Objectives
● To understand various intellectual property rights
● To understand the procedure for applying copyright, patents.
● Learn the legalities of intellectual property to avoid plagiarism and other IPR related crimes like
copyright infringements.
● To understand various cybercrimes.
● To understand the information technology act.
● To understand various penalties related to cybercrimes.
Syllabus
Fundamentals of IPR - Patents - Trademarks - Copyright - Industrial Designs - Geographic Indications
- Trade Secret and software copyright - cyber law - Information Technology Acts and Punishments
Expected Outcome
Suggested MOOC
1. http://www.ficciipcourse.in/index.php
2. https://onlinecourses.nptel.ac.in/noc16_hs08/preview
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA365 Elective II- Cyber Forensics 3-1-0-4 2016
Course Objectives
Syllabus
Computer forensics fundamentals - Types of computer forensics technology - Data recovery - Evidence
collection and data seizure - Computer image verification and authentication - Reconstructing past events
Expected Outcome
References
1. John R Vacca,”Computer Forensics computer crime scene investigation “, Firewall Media, 2009
Edition Reprint 2012.
2. Bill Nelson, Amelia Phillips, Christopher Steuart , “Guide to Computer Forensics and
Investigations”, Cengage Learning, Fifth Edition 2010.
3. Marjie T. Britz, “Computer Forensics and Cyber Crime”, Pearson Third Edition 2013.
4. Marie - Helen Maras “Computer Forensics: Cybercriminals, Laws, and Evidence”, Jones & Bartlett
Learning, Second Edition 2015.
Suggested MOOC
1. http://www.open.edu/openlearn/futurelearn/cyber-security
2. http://www.cyberdegrees.org/resources/free-onlinecourses/.
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
//Lab exercises may be given for (use any open source tools):
1. Investigating NTFS Drive using DiskExplorer.
2. Viewing contents of a forensic image
III 8 15
//Lab exercises may be given for (use any open source tools):
1. File Recovery.
2. Data Recovery.
Evidence collection and data seizure: Why collect evidence?, Collection
options - Obstacles - Types of evidence - The rules of evidence - Volatile
evidence - General procedure - Collection and archiving - Methods of
collection - Artifact - Collection steps. Preserving the digital crime scene -
Computer evidence processing scene - Legal aspects of collecting forensic
IV evidence. 10 20
// Lab Exercises may be given for (use any open source tools):
1. Gathering evidences
2. Viewing files of various formats
// Lab Exercise may be given for (use any open source tools):
1. Identifying image file format.
2. Analyzing images for hidden messages.
SECOND INTERNAL EXAM
Reconstructing past events: How to become a digital detective - Useable
file formats - Unusable file formats - Converting files. Network forensics
scenario - A technical approach - Destruction of e-mail - Damaging
computer evidence.
// Lab Exercises may be given for (use any open source tools):
VI 10 20
1. Cracking password using any password recovery tool.
2. Recovering deleted emails using the recover my email utility
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA367 Elective II- Internet of Things 3-1-0-4 2016
Course Objectives
Syllabus
IoT ecosystem concepts and architectures - IoT enablers and solutions - IoT data and knowledge
management - IoT reliability, security, and privacy - IoT applications
Expected Outcome
● At the end of the course, students should be able to understand the concepts and features of IoT
Paradigm with a good understanding on different IoT architectures and how it is practically
managed.
References
1. Rajkumar Buyya; Amir Vahid Dastjerdi , “Internet of Things”, Morgan Kaufmann, 2016
2. Peter Waher, “Learning Internet of Things”, Packt Publishing, 2015
3. S. Sitharama Iyengar; Nandan Parameshwaran; Vir V. Phoha; N. Balakrishnan; Chuka D. Okoye,
“Fundamentals of Sensor Network Programming: Applications and Technology”, Wiley,
December 14, 2010
4. Robert Stackowiak (Author), Art Licht (Author), Venu Mantha (Author), Louis Nagode (Author),
“Big Data and The Internet of Things: Enterprise Information Architecture for A New Age” ,
Apress, 2015
Suggested MOOC
1. https://www.coursera.org/specializations/internet-of-things
2. http://web.mit.edu/professional/digital-programs/courses/IoT
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA369 Elective II- Python Programming 3-1-0-4 2016
Course Objectives
Syllabus
Introduction to Python, Data Types and Operations, Decision Making, Functions, Modules & Packages,
File Handling, Object Oriented Programming, Exception Handling and Regular Expressions, Database
Programming, GUI Programming, Web Development and Web Frameworks.
Expected Outcome
Suggested MOOC
1. https://archive.org/details/MIT6.00SCS11
2. https://www.coursera.org/course/pythonlearn
3. http://www.learnerstv.com/Free-Computer-Science-Video-lectures-ltv163-Page1.htm
4. https://www.coursera.org/learn/python-databases
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B
(Essay) together from a single module, not to exceed the marks assigned to
that module specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA371 Elective II- Social Network Analysis 3-1-0-4 2016
Course Objectives
● To provide students with essential knowledge of network analysis applicable to real world data,
with examples from today’s most popular social networks.
Syllabus
Introduction to Social Network Analysis - Social Media Examples - Electronic Sources for Network Analysis
- Mathematical Representations of Social Networks - Modelling and Aggregating Social Network Data -
Semantic based Social Network Analysis - Case Studies
Expected Outcome
References
1. Peter Mika, “Social Networks and the Semantic Web”, Springer, 2007
2. Hansen, Derek, Ben Shneiderman, Marc Smith, “Analyzing Social Media Networks with
NodeXL: Insights from a Connected World”, Morgan Kaufmann, 2011
3. Stanley Wasserman and Katherine Faust. "Social Network Analysis. Methods and Applications."
Cambridge University Press, 1994
4. Christina Prell, “Social Network Analysis: History, Theory and Methodology”, SAGE Publications
Ltd, 2012
Suggested MOOC
1. http://nptel.ac.in/courses/106106146
2. https://www.politaktiv.org/documents/10157/29141/SocNet_TheoryApp.pdf
3. https://www.mooc-list.com/course/social-network-analysis-coursera
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M). There will
be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with an
alternative choice question from the same module (6 x 6M=36M).The maximum
number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA381 Elective III- Cloud Computing 3-1-0-4 2016
Course Objectives
Syllabus
Introduction to Cloud Computing - The Value Proposition of Cloud computing - Using Cloud Platforms -
Exploring Cloud Infrastructures - Details of Cloud Services and its Applications - Using the Mobile Cloud
Expected Outcome
● At the end of the course, students should be able to understand the basics of Cloud computing
and be able to would be able to understand different cloud offering and its applications.
Text Book
1. Peter Waher, “Cloud Computing Bible”, John Wiley & Sons Publishing, 2011
Reference Books
1. Michael Kavis, "Architecting the Cloud: Design Decisions for Cloud Computing Service Models
(SaaS, PaaS, and IaaS)", John Wiley & Sons Publishing, 2014
2. Jothy Rosenberg; Arthur Mateos, “The Cloud at Your Service: The when, how, and why of
enterprise cloud computing”, Manning Publications , 2010
Suggested MOOC
1. https://www.coursera.org/specializations/cloud-computing
2. http://ocw.mit.edu/courses/sloan-school-ofmanagement/15-768-management-of-services-
conceptsdesign-and-delivery-fall-2010/lecture-notes/
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA383 Elective III- Human Computer Interaction 3-1-0-4 2016
Course Objectives
● Acquire the knowledge and skills needed to create highly usable software systems.
● Obtain the objective of the basics of human and computational abilities and limitations.
Syllabus
Usability Engineering Concepts - Interaction basics - Interaction Designs - Socio - Organizational Issues
and Stakeholder Requirements - Modelling Rich Interaction
Expected Outcome
References
1. Alan Dix, Janet Finlay, ”Human Computer Interaction” ,Third Edition,Pearson Education
2. Preece J. , Rogers Y, Sharp H.,”Human Computer Interaction, Addison - Wesley,1994.
3. Martin.G.Helander, Thomas .k .Landauer, “Handbook of Human Computer Interaction”, Second
Edition , Elsevier 1997
4. B.Shneiderman, “ Designing The User Interface” Addison Wesley 2000
Suggested MOOC
1. http://nptel.ac.in/courses/106103115/3
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA385 Elective III- Bioinformatics 3-1-0-4 2016
Course Objectives
Syllabus
Introduction to bioinformatics and molecular biology: Databases tools and their uses, Data searches and
Pairwise Alignments, Molecular Phylogenetic, Genomics and Gene Recognition, Protein and RNA structure
Prediction
Expected Outcome
● At the end of the course, Students will be comfortable to formulate solutions to problems in the
field of bioinformatics.
References
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
Molecular Phylogenetic:
Introduction, Advantages, Phylogenetic Trees, Distance Matrix methods,
Maximum likelihood approaches, Multiple sequence alignments
Molecular visualization tools:
IV Sequence viewers (Artemis, SeqVISTA), 10 20
3D structure viewers (Rasmol, SPDBv, Chime, Cn3D, PyMol) and
Anatomical visualization tools.
//Tutorials may be given to familiarize the tools like Rasmol, Chime etc
Genomics and Gene Recognition:
General introduction to Gene expression in prokaryotes and eukaryotes-
V Prokaryotic Genomes – Gene structure, GC content, Gene Density, 8 15
Eukaryotic Genomes- Gene structure, GC content, Gene Density -
Gene Expression, Transposition
SECOND INTERNAL EXAM
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA387 Elective III- Computer Graphics 3-1-0-4 2016
Course Objectives
● Provide a comprehensive introduc on to the basic hardware and so ware elements of computer
graphics.
● Provide a thorough explana on of computer graphics techniques such as geometric transformation,
projections, hidden surface elimination, illumination models and 3D rendering.
● Provide an insight into graphics applica ons and mul media components.
Syllabus
Introduction: What is Computer Graphics? Basic Raster Graphics: Scan conversion, filling, and clipping
Geometric Manipulation: Transformations, Matrices, Homogeneous Coordinates. Elementary 3D
Graphics: Plane projections, Vanishing points, Specification of a 3D view. Visibility: Image and object
precision, z-buffer algorithms, area based algorithms. Rendering: Lighting, Radiosity, Raytracing
Expected Outcome
At the end of the course, Students will be able to
1. Describe underlying graphic hardware, architecture, graphic primitives and their attributes and apply
algorithms for implementing (drawing) these primitives.
2. Develop applications applying mathematical concepts of geometric transformations, polygon filling
and clipping in 2 dimensions.
3. Compare the different types of projections of 3D objects and the methods to identify visible surfaces
of those projected images, rendering them using illumination models.
References
1. Donald Hearn and M. Pauline Baker, “Computer Graphics – C Version”, Pearson Education, 2nd Edition
2. Sinha, Udai, “Computer Graphics”, TMH, 2010
3. David F. Rogers, “Procedural Elements for Computer Graphics”, McGraw Hill
4. F.S. Hill., “Computer Graphics Using Open GL”, Prentice Hall, 2001
5. S. Feiner, J. Foley, A. Van Dam, R. Hughes, “Computer Graphics, Principles and Practice”, Addison
Wesley, 1990.
4. John F. Koegel Buford, “Multimedia systems”, Pearson Education/Addison Wesley.
5. Tay Vaughan, “Multimedia making it works”, TMH, 6th Ed.2004
6. William M. Newman and Robert F. Sproull, “Principles of Interactive Computer Graphics”, McGraw Hill
7. Desai, “Computer Graphics”, PHI
Suggested MOOC
1. http://nptel.ac.in/courses/106106090
2. http://www.learnerstv.com/Free-Computer-Science-Video-lectures-ltv046-Page1.htm
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA389 Elective III- Parallel and Distributed Computing 3-1-0-4 2016
Course Objectives
Syllabus
Introduction, Shared memory model (Thread based) - OpenMP, Shared memory model (Thread based) -
CUDA, Shared memory model (Process based) : System V, Distributed Model - MPI, Hybrid Model :
OpenMP + MPI, Data Parallel Model (PGAS) : UPC, Measuring the Performance, The Linpack Benchmark
Expected Outcome
● Analyse a problem, find out the scope of parallelising it and to write parallel programs
● The ability to convert existing serial programs to parallel ones, if possible
● Applying various programming models in solving the problems
References
Suggested MOOC
1. https://computing.llnl.gov/tutorials/parallel_comp/
2. http://www.openmp.org/wp-content/uploads/OpenMP3.1.pdf
3. http://docs.nvidia.com/cuda/cuda-c-programming-guide/
4. https://docs.oracle.com/cd/E19683-01/816-5042/svipc-41256/index.html
5. http://mpi-forum.org/docs/mpi-3.0/mpi30-report.pdf
6. http://upc.lbl.gov/publications/upc-lang-spec-1.3.pdf
7. http://www.gccupc.org/gnu-upc-info/binary-release
8. https://www.top500.org/lists/2016/11/download/TOP500_201611.xls
9. https://www.top500.org/green500/
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
Writing a UPC program to find mean deviation. Using gnu UPC compiler.
SECOND INTERNAL EXAM
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLIMCA391 Elective III- Artificial Intelligence 3-1-0-4 2016
Course Objectives
Syllabus
Introduction to AI and Production Systems, Search Strategies, Game playing, Knowledge Representation
Structures, Knowledge representation using Logic, Planning, Learning, Expert systems, Fuzzy Logic
Expected Outcome
● Ability to design Algorithms using AI techniques to solve problems that are otherwise
intractable.
● Ability to design and develop expert systems
Text Books
References
1. Peter Jackson, “Introduction to Expert Systems”, 3rd Edition, Pearson Education, 2007.
2. Dan W. Patterson, “Introduction to AI and ES”, Pearson Education, 2007.
Suggested MOOC
1. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-
intelligence-fall-2010/lecture-videos/
2. http://nptel.ac.in/courses/106105077/
Course Plan
End-Semester
% of marks in
Examination
Module
Hours
Contents
Allotted
There will be two parts in the Question paper - Part A and Part B.
Part A will have 8 short answer questions of 3 marks each (8 X 3 M = 24 M).
There will be no choice questions.
Part B will have 6 essay questions one from each module of 6 marks each, with
an alternative choice question from the same module (6 x 6M=36M).The
maximum number of sub part questions in Part B to be limited to 2.
The total marks assigned to questions in Part A (Short answer) and Part B (Essay)
together from a single module, not to exceed the marks assigned to that module
specified in the course plan in the syllabus.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLMCA341 SEMINAR 0-0-2-2 2016
Course Objectives
To enable the students to gain knowledge in any of the technically relevant current topics on computer
science/information technology/research, and acquire the confidence in presenting the topic and
preparing a report.
Syllabus
Guidelines
The student shall undertake detailed study on a technically relevant current topic in computer
science/information technology under the supervision of a faculty member, by referring articles
published in reputed journals/conference proceedings. Each student has to submit a seminar report,
based on these papers; the report must not be reproduction of any original paper. The topic shall be
presented in the class taking a duration of 15-20 minutes.
The report and slides for presentation shall be prepared using free typesetting software such as LATEX. A
committee consisting of three/four faculty members shall evaluate
the seminar presentation.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLMCA351 MINI PROJECT 0-0-8-2 2016
Course Objectives
References
1. Alistair Cockburn, “Agile Software Development: The Cooperative Game”, Addison Wesley, 2nd
Edition (2006).
2. Andrew Hunt, David Thomas, “The Pragmatic Programmer: From Journeyman to Master”,
Pearson India, 1st Edition (2008).
3. Ken Schwaber, Mike Beedle, “Agile Software Development with Scrum”, Pearson (2008).
4. Lisa Crispin, Janet Gregory, “Agile Testing: A Practical Guide for Testers and Agile Teams”,
Addison Wesley Professional, 1st Edition (2008).
5. Mike Cohn, “User Stories Applied: For Agile Software Development”, Addison Wesley, 1st
Edition, (2004).
6. Pressman, R.S., “Software Engineering: A Practitioner's Approach”, McGraw Hill SE, 7th Edition,
(2010).
7. Robert C. Martin, “Agile Software Development, Principles, Patterns and Practices”, Prentice Hall
Imprint, Pearson Education, 2nd Edition (2002).
8. Rod Stephens, “Beginning Software Engineering”, Wrox Series, Wiley India Pvt Ltd (2015).
9. RyPress “Ry's Git Tutorial” (Free e-book)
Suggested MOOC
1. Introduction to DevOps(https://www.edx.org/course/introduction-devops-microsoft-dev212x)
Week Schedule
Familiarisation with build tools.
Familiarisation with an IDE (Eclipse, NetBeans,...), that support build tools and git.
I
Selection of Topic, Formation of Development Team, Feasibility analysis.
Topic Approval, Meeting of Development Team including Scrum Master with Product Owner.
Informal, preliminary discussions of requirements. Creating user stories in the rough record.
II
Commencement of the Project.
Identifying modules, Initial Design of Database & UI. Starting Test Driven Development.
Creating an empty git repository by Scrum Master / one member of the Development team.
Setting permission to other members. Pushing the first version of the Project along with a
III
Readme file containing contact details of team members.
Using Branch for individual members. Merging with Master.
Year of
Course No. Course Name L-T-P Credits
Introduction
RLMCA352 PROJECT AND VIVA-VOCE 0-0-30-12 2016
Course Objectives
Note:
Identify Real projects - Any project useful to the Society. The project must be done in house. The student
has to spent the time in the lab for project work. Attendance as per MCA regulations is applicable for
appearing for the final viva-voce. However the evaluation committee can give consent to students in
exceptional cases to do their project in Industry which has real live projects. Local industries and training
Institutes which offer live projects should not be permitted.
Students, individually have to do a project approved by their faculty Supervisor. Project evaluation weights
shall be as follows:-For convenience the marks are allotted as follows.
A faculty/technical staff should act as the Scrum Master of each Project team. The Customer or a Senior
faculty is the Product Owner.
Frequent meetings are highly encouraged, at the convenience of the Scrum Master. Should not exceed 15
minutes. Ensure meetings once in three days. A sprint is two weeks, so ensure biweekly reviews. A review
should not exceed 30 minutes. A demo to the Product Owner is compulsory in each review.
Follow Test Driven Development. Bugzilla or an equivalent tool may be used for bug tracking.
The student should keep a rough record. Divide it into 4 parts. Product Backlog, Database & UI Design,
Testing & Validation and details of Versions. Make dated entries to the corresponding part, as the project
progresses. The Corrections and comments from Product Owner/Scrum Master should be clearly indicated
with the Date.
Project presentations may be conducted for Internal Assessment. They should also serve as supplement to
Scrum reviews. The evaluation board may consist of other faculty members/technical staff. A maximum of
2 Presentations are allowed. Scrum reviews should not be sacrificed for presentations.
Students must be encouraged to publish their work in journals and due credit to be given to the students
for this.
Latex or an equivalent tool should be used for preparing Presentations and Project Report.
Week Schedule
Topic Approval, Meeting of student and Scrum Master with Product Owner. Informal,
II preliminary discussions of requirements. Creating user stories in the rough record.
Commencement of the Project.
Identifying modules, Initial Design of Database & UI. Starting Test Driven Development.
Creating an empty git repository by Scrum Master / Student. Pushing the first version of the
III
Project along with a Readme file containing contact details of team members.
Using Branch for individual members. Merging with Master.