DSA Presentstio
DSA Presentstio
DSA Presentstio
1. Which data structure allows deleting data elements from front and inserting
at rear?
A. Stacks
B. Queues
C. Deques
2. Identify the data structure which allows deletions at both ends of the list but
insertion at only one end
A. Input-restricted deque
B. Output-restricted deque
C. Priority queues
D. None of above
A. Strings
B. Lists
C. Stacks
D. None of above
A. Strings
B. Lists
C. Queues
D. All of above
A. Deque
B. Priority
C. Tree
D. All of above
6. A binary tree whose every node has either zero or two children is called
D. None of above
A. Dn = n log2n
B. Dn = n log2n+1
C. Dn = log2n
D. Dn = log2n+1
10. When converting binary tree into extended binary tree, all the original nodes
in binary tree are
D. None of above
1. The post order traversal of a binary tree is DEBFCA. Find out the pre order
traversal
A. ABFCDE
B. ADBFEC
C. ABDECF
D. ABDCEF
A. Bubble sort
B. Insertion sort
C. Quick sort
D. All of above
A. Sub algorithm
B. Recursion
C. Polish notation
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D. Traversal algorithm
4. In a binary tree, certain null entries are replaced by special pointers which
point to nodes higher in the tree for efficiency. These special pointers are called
A. Leaf
B. branch
C. path
D. thread
5. The in order traversal of tree will yield a sorted listing of elements of tree in
A. Binary trees
C. Heaps
D. None of above
6. In a Heap tree
A. Values in a node is greater than every value in left sub tree and smaller
than right sub tree
A. endpoints of e
B. adjacent nodes
C. neighbors
D. all of above
A. a tree graph
B. free tree
C. a tree
D. All of above
D. both b and c
A. isolated
B. complete
C. finite
D. strongly connected
A. Counting microseconds
A. Best case
B. Worst case
C. Average case
D. Null case
D. When Item is the last element in the array or is not there at all
C. Sometimes more complicated and some other times simpler than that of
worst case
D. None or above
A. O(n)
B. O(log n)
C. O(n^2)
D. O(n log n)
A. O(n)
B. O(log )
C. O(n^2)
D. O(n log n)
A. O(n)
B. O(log n)
C. O(n^2)
D. O(n log n)
2. In a Stack the command to access nth element from the top of the stacks will
be
A. S[Top-n]
B. S [Top+n]
C. S [top-n-1]
3. If yyy, xxx and zzz are the elements of a lexically ordered binary tree, then in
preorder traversal which node will be traverse first
A. xxx
B. yyy
C. zzz
4. In a balance binary tree the height of two sub trees of every node can not
differ by more than
A. 2
B. 1
C. 3
A. 0
B. 5
C. 10
D. 15
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A. 2
B. 5
C. 3
A. O(n log n)
B. O(2n)
C. O(n^2)
9. Write the out put of the following program: int a[] = {1,2,3}*P;
A. 3
B. Junk value
10. If the out degree of every node is exactly equal to M or 0 and the number of
nodes at level K is Mk-1 [consider root at level 1], then tree is called as (i) Full m-
ary try (ii) Complete m-ary tree (iii)Positional m-ary tree
A. Only (i)
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B. Only (ii)
1. If all c(i, j )’s and r(i, j)’s are calculated, then OBST algorithm in worst case takes
one of the following time.
A. O(n log n)
B. O(n^3)
C. O(n^2)
D. O(log n)
E. O(n^4).
A. O(n)
B. O(n log n)
C. O(1)
D. O( log n)
E. O(n^2).
A. O(n log n)
B. O( log n)
C. O(n^2)
D. O(n)
E. O(1).
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B. Top-down approach
C. Bottom-up approach
D. Hierarchical approach
E. Heuristic approach.
5. What do you call the selected keys in the quick sort method?
A. Outer key
B. Inner Key
C. Partition key
D. Pivot key
E. Recombine key.
B. By the sum of the costs of the edges and vertices of the tree
E. By the sum of the costs of the edges and vertices of the graph.
7. The time complexity of the normal quick sort, randomized quick sort
algorithms in the worst case is
B. O(n^2), O(n^2)
8. Let there be an array of length ‘N’, and the selection sort algorithm is used to
sort it, how many times a swap function is called to complete the execution?
A. N log N times
B. log N times
C. N2 times
D. N-1 times
E. N times.
A. Bubble sort
B. Quick sort
C. Merge sort
D. Radix sort
E. Selection sort
A. Central tendency
B. Differential equation
C. Order of execution
D. Order of magnitude
E. Order of Storage
A. log2 n + 1
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B. n
C. 2n
D. log n.
3. For defining the best time complexity, let f (n) = log n and g (n) = √n, _________
A. O (100 Log N)
C. O (N logN)
D. O (N2).
5. Let f, t: N→R 0, and t (n) O (f (n)) iff t(n)≤ c.f (n) where cis positive real
constant and n≥ no, then no is ___________
A. Upper bound
B. Lower bound
C. Duality value
D. Threshold value
E. Maximum value.
A. 1
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B. 2
C. 3
D. 4
C. Is same as backtracking
8. Which method of traversal does not use stack to hold nodes that are waiting
to be processed?
A. Dept First
B. D-search
C. Breadth first
D. Back-tracking
9. The Knapsack problem where the objective function is to minimize the profit
is ______
A. Greedy
B. Dynamic 0 / 1
C. Back tracking
10. Choose the correct answer for the following statements: I. The theory of NP–
completeness provides a method of obtaining a polynomial time for NP
algorithms. II. All NP-complete problem are NP-Hard.
1. The Hamiltonian cycles problem uses the following line of code to generate a
next vertex, provided x[ ] is a global array and kth vertex is under consideration:
A. O(mnm)
B. O(nm)
C. O(nm. 2n)
D. O(nmn).
3. For 0/1 KNAPSACK problem, the algorithm takes ________ amount of time for
memory table, and ______time to determine the optimal load, for N objects and
W as the capacity of KNAPSACK.
A. O(N+W), O(NW)
B. O(NW),O(N+W)
C. O(N),O(NW)
D. O(NW),O(N)
A. Insertion
B. Selection
C. Deletion
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D. Exchange
5. What is the type of the algorithm used in solving the 8 Queens problem?
A. Backtracking
B. Dynamic
D. D and C
6. The following are the statements regarding the NP problems. Chose the right
option from the following options: I. All NP-complete problems are not NP-hard.
II. Some NP-hard problems are not known to be NP-complete.
7. Let G be a graph with ‘n’ nodes and let ‘m’ be the chromatic number of the
graph. Then the time taken by the backtracking algorithm to color it is
A. O(nm)
B. O(n+m)
C. O(mnm)
D. O(nmn).
A. O(n2)
B. O(n4)
C. O(n3)
D. O(n)
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E. O(n log n ).
9. Read the following statements carefully and pick the correct option: I. The
worst time complexity of the Floyd’s algorithm is O(n3). II. The worst time
complexity of the War shall’s algorithm is O(n3).
10. The asymptotic notation for defining the average time complexity is
A. Equivalence
B. Symmetric
C. Reflexive
1. For the bubble sort algorithm, what is the time complexity of the best/worst
case? (assume that the computation stops as soon as no more swaps in one
pass)
2. For the quick sort algorithm, what is the time complexity of the best/worst
case?
3. In an arbitrary tree ( not a search tree) of order M. Its size is N, and its height is
K. The computation time needed to find a data item on T is
A. O(K*K)
B. O(M*M)
C. O(N)
D. O(K)
B. Knapsack problem
C. Selection problem
D. Merge sort
E. Quick sort.
A. Limit rule
B. Rule of inference
C. Duality rule
D. Rule of consequences
A. O(1)
B. O(log n)
C. O(n2)
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D. O(n)
7. Find the odd one out from the following categories of algorithms.
A. TVSP
B. N-Queens
C. 15-Puzzle
D. Bin-Packing.
8. The time complexity of binary search in best, worst cases for an array of size N
is
A. N, N2
B. 1, Log N
C. Log N, N2
D. 1, N log N
9. Which of following algorithm scans the list by swapping the entries whenever
pair of adjacent keys are out of desired order?
A. Insertion sort
B. Quick sort
C. Shell sort
D. Bubble sort
10. The mathematical definition for Omega can be defined as, provided f,g:NR+
and c is a positive constant and n > n0,
A. f(n) ≥ c. g(n) n
B. f(n) = c. g(n) n
C. f(n) ≥ c + g(n) n
D. f(n) = c + g(n) n
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1. The notation is
A. Symmetric
B. Reflexive
C. Transitive
2. From the following choose the one which belongs to the algorithm paradigm
other than . to which others from the following belongs to.
B. Knapsack problem
C. Selection problem
D. Merge sort
3. Identify the name of the sorting in which time is not proportional to n2.
A. Selection sort
B. Bubble sort
C. Quick sort
D. Insertion sort
A. Principle of Duality
B. Principle of Feasibility
C. Principle of Optimality
D. Principle of Dynamicity.
5. Which of the following versions of merge sort algorithm does uses space
efficiently?
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A. Contiguous version
B. Array version
C. Linked version
D. Structure version
E. Heap version.
6. Identify the correct problem for multistage graph from the list given below.
D. Barber’s problem
7. How many edges are there in a Hamiltonian cycle if the edge cost is ‘c’ and the
A. c
B. cn
C. n
D. 2c
A. L ≈ NP
B. L α NP
C. L ε NP
D. L = NP
9. What would be the cost value for any answering node of a sub tree with root
‘r’ using branch-bound algorithm?
A. Maximum
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B. Minimum
C. Optimal
D. Average
10. From the following choose the one which belongs to the algorithm paradigm
other than . to which others from the following belongs to.
B. Knapsack problem
C. Selection problem
D. Merge sort
11. Identify the name of the sorting in which time is not proportional to n2.
A. Selection sort
B. Bubble sort
C. Quick sort
D. Insertion sort
A. Principle of Duality
B. Principle of Feasibility
C. Principle of Optimality
D. Principle of Dynamicity.
13. Which of the following versions of merge sort algorithm does uses space
efficiently?
A. Contiguous version
B. Array version
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C. Linked version
D. Structure version
E. Heap version.
14. Identify the correct problem for multistage graph from the list given below.
D. Barber’s problem
15. How many edges are there in a Hamiltonian cycle if the edge cost is ‘c’ and
the
A. c
B. cn
C. n
D. 2c
A. L ≈ NP
B. L α NP
C. L ε NP
D. L = NP
17. What would be the cost value for any answering node of a sub tree with root
‘r’ using branch-bound algorithm?
A. Maximum
B. Minimum
C. Optimal
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D. Average
1. Name the node which has been generated but none of its children nodes have
been generated in state space tree of backtracking method.
A. Dead node
B. Live node
C. E-Node
D. State Node
2. How many nodes are there in a full state space tree with n = 6?
A. 65
B. 64
C. 63
D. 32
3. This algorithm scans the list by swapping the entries whenever pair of
adjacent keys are out of desired order.
A. Insertion sort.
B. Bubble sort.
C. Shell sort.
D. Quick sort.
4. The notation is
A. Symmetric
B. Reflexive
C. Transitive
D. B & C only
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5. From the following chose the one which belongs to the algorithm paradigm
other than to which others from the following belongs to.
B. Knapsack problem.
C. Selection problem.
D. Merge sort.
6. To calculated (i, j )’s, w( i, j)’s and r(i, j)’s; the OBST algorithm in worst case takes
the following time.
A. O(log n)
B. O (n4)
C. O (n3)
D. O (n log n)
7. What is the type of the algorithm used in solving the 4 Queens problem?
A. Greedy
B. Dynamic
D. Backtracking.
8. In Knapsack problem, the best strategy to get the optimal solution, where Pi,
Wi is the Profit, Weight associated with each of the Xith object respectively is to
A. O(N)
B. Ω( n log n)
C. O (n2 log n)
D. O ( n log n)
10. The divide and conquer merge sort algorithm’s time complexity can be
defined as
A. (long n)
B. (n)
C. Ω (n log n)
D. (n log n)
B. Central tendency
C. Differential equation
D. Polynomial equation
A. log2 n + 1
B. n
C. N^2
D. 2^n
A. Sequential search
B. Binary search
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C. Indexed search
D. Hashing
C. Is same as backtracking
5. Which of the following searching methods requires that all keys must reside in
internal memory?
A. Binary search
B. Sequential search
C. Hashing
A. Ω (n³)
B. Ω (n²)
C. Ω (n)
D. Ω (35)
A. Constant
C. Logarithmic
D. Linear
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A. θ (n^2)
B. θ (8)
C. θ (log n)
D. θ (n)
A. Sequence
B. Selection
C. Repetition
1. When we say an algorithm has a time complexity of O (n), what does it mean?
2. Can we read a data item at any location of a list within a constant time (i.e.
O(1))?
A. Yes
3. Sequential search has a time complexity of O(n), and binary search has a time
complexity of O(log(n)). What difference will it make when the size n is 1000?
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A. You would not notice much difference because computers run very fast
anyway
4. Read the following statements carefully, and choose the correct answer. I. The
Ω notation is Anti Symmetric. II. The big Oh notation is Semi Equivalence.
A. Merge Sort
B. TVSP Problem
C. KnapSack Problem
D. OBST Problem
6. How many minimum number of spanning trees, one can have from a given
connected graph with N nodes is having different weights for the edges.
A. N-1
B. One
C. 1/(N+1) 2NCN
D. 2NCN
7. The mathematical definition for Omega can be defined as, provided f,g:NR+
and c is a positive constant and n > n0,
A. f(n)≥ c. g(n) n
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B. f(n) £ c. g(n) n
C. f(n) ≥ c + g(n) n
D. f(n) £ c + g(n) n
E. f(n) £ g(n) n.
8. The OBST algorithm in worst case takes _______ time if all c(i, j )’s and r(i, j)’s are
calculated.
A. O(log n)
B. O(n^4)
C. O(n^3)
D. O(n log n)
10. Breadth first search uses __________ as an auxiliary structure to hold nodes
for future processing.
A. Stack
B. Linked list
C. Graph
D. Queue
1. From the following pick the one which does not belongs to the same paradigm
to which others belongs to.
B. Knapsack problem
C. Selection problem
D. Merge sort
B. Dynamic programming
C. Greedy method
A. Space complexity
B. Worst case
C. Time complexity
D. Best case
A. Space complexity
B. Worst case
C. Time complexity
D. Best case
5. __________ is the minimum number of steps that can executed for the given
parameters
A. Average case
B. Worst case
C. Time complexity
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D. Best case
6. __________ is the maximum number of steps that can executed for the given
parameters
A. Average case
B. Worst case
C. Time complexity
D. Best case
7. __________ is the average number of steps that can executed for the given
parameters
A. Average case
B. Worst case
C. Time complexity
D. Best case
A. O(n)
B. O(logn)
C. Ɵ(nlogn)
D. Ɵ(logn)
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A. O(n)
B. Ɵ(nlogn)
C. O(logn)
D. Ɵ(logn)
A. O(n)
B. Ɵ(nlogn)
C. O(logn)
D. Ɵ(logn)
A. CARHOARE
B. HAMILTON
D. STRASSEN
A. CARHOARE
B. HAMILTON
D. STRASSEN
A. O(n^2log7)
B. O(nlogn)
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C. O(n^2)
D. O(logn)
A. O(n^2logn)
B. O(nlogn)
C. O(logn)
D. O(logn2)
A. Ɵ (nlogn)
B. O(logn)
C. O(nlogn)
D. Ɵ(logn)
7. Which design strategy stops the execution when it find the solution otherwise
starts the problem from top
A. Back tracking
D. Dynamic programming
A. Pseudo-code
B. Graph Coloring
C. Flow Chart
D. Dynamic programming
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A. input
B. Read
C. Write
D. Return
A. input
B. Read
C. Write
D. Return
A. Time Complexity
B. Input
C. Space Complexity
D. Finiteness
A. Time Complexity
B. Input
C. Space Complexity
D. Finiteness
A. Constant
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B. Quadratic
C. Linear
D. Cubic
A. Constant
B. Quadratic
C. Linear
D. Cubic
A. Constant
B. Quadratic
C. Linear
D. Cubic
A. Exponential
B. Quadratic
C. Linear
D. Cubic
A. Constant
B. Quadratic
C. Linear
D. Exponential
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A. Graphic card
B. Data Processing
C. Tape sorting
D. Card Sorting
A. Graphic card
B. Networking
C. Card Sorting
D. Data Processing
10. The method will choosing when sub problems share sub problems
B. Greedy method
C. Dynamic programming
D. Back tracking
1. Time complexity of given algorithm Algorithm Display (A) { For I:=0 to n-1 { For
J:=0 to n-1 { Write A; } } }
A. 2n^2+4n+4
B. 2n^2+n
C. 2n^2+4n+2
D. 2n^2-1
2. The sorting , which works very well for small file is ______________
A. Count sort
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B. Selection sort
C. Merge sort
D. Quick sort
A. External sorting
B. Insertion sorting
C. Internal sorting
D. Exponential sorting
A. Program
B. Algorithm
C. Greedy Method
D. Problem
D. Simple calculations
A. C=5
B. C=12
C. C=6
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D. C=11
A. C=5
B. C=12
C. C=6
D. C=11
8. The functions f &g are non-negative functions. The function f(n)=O(g(n)) if and
only if there exist positive constants c& n0 such that __________ for all n, n≥ n0
A. f(n)≤C*g(n)
B. f(n) = C*g(n)
C. f(n) ≥ C*g(n)
D. f(n) != C*g(n)
9. The functions f & g are non-negative functions. The function f(n)=Ω(g(n)) if and
only if there exist positive constants c& n0 such that ___________ for all n, n≥ n0
A. f(n) ≤ C*g(n)
B. f(n) = C*g(n)
C. f(n) ≥ C*g(n)
D. f(n) != C*g(n)
10. The functions f & g are non-negative functions. The function f(n)=θ(g(n)) if
and only if there exist positive constants c1,c2 & n0 such that ________for all n, n≥
n0
A. Ω
B. Θ
C. Ω
D. O
A. Ω
B. Θ
C. ω
D. O
A. Ω
B. Θ
C. ω
D. O
A. Little oh
B. Little omega
C. Big oh
D. Omega
A. Little oh
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B. Little omega
C. Big oh
D. Omega
A. Output
B. Finiteness
C. Effectiveness
D. Input
A. Output
B. Finiteness
C. Effectiveness
D. Input
A. Output
B. Definiteness
C. Effectiveness
D. Input
A. Output
B. Finiteness
42
C. Effectiveness
D. Input
A. Input
B. Output
C. Time complexity
D. Best case
A. Input
B. Output
C. Time complexity
D. Effectiveness
A. 4n+4
B. 4n^2+4
C. 2n^2+2n+2
D. 4n+4
3. Time complexity of given algorithm Algorithm Sum(A,S) { for i:=1 to n-1 { for
j:=2 to n-1 { S:=S+i+j; return S; } } }
A. 6n^2-14n+4
B. 4n^2+6n+12
C. 6n^2+14n+10
D. 6n^2-14n+10
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B. Greedy method
C. Dynamic programming
B. Dynamic programming
C. Greedy method
B. Spanning tree
D. None of these
7. which is not feasible solution in the case of job sequence problem item : 1 2 3
4 profit : 100 10 15 27 deadline : 2 1 2 1
A. (1,4)
B. (4,3)
C. (2,4)
D. (1,2)
A. (1,3,4)
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B. (4,2,3)
C. (1,2,4)
D. (1,5,2)
A. (1,5,6,4)
B. (7,6,4,3)
C. (2,3,1,7)
D. (1,2,3,4)
A. 498
B. 480
C. 499
D. 485
A. 345
B. 384
C. 354
D. 350
A. O(|V|)
B. O(|E|)
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C. O(|V|+|E|)
D. O(|V2|)
4. In the case of Fibnocci heap the running time of Prim’s algorithm is _________
A. O(E log V)
B. O(V log E)
C. O( log V)
D. O(E log E)
A. O(|V|)
B. O(|E|)
C. O(|V|+|E|)
D. O(|V2|)
A. O(E log V)
B. O(VlogE)
C. O(V2)
D. O(logE)
A. O(E log V)
B. O(V2)
C. O(nlog7)
D. O(log n7)
A. p1=(a+d)(e+h)
B. p3=(a-c)(e+f)
C. p2=(-e+g)d
D. p4=(a+b)h
A. p1=(a+d)(e+h)
B. p3=(a-c)(e+f)
C. p7=(-e+g)d
D. p4=(a-b)h
B. High accuracy
A. 3n/2
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B. n/4
C. n/2
D. n-1
A. 3n/2
B. n/4
C. n/2
D. n-1
A. 3n/2
B. n/4
C. n/2
D. n-1
5. The method which stops the execution ,if it find the solution. Otherwise it start
from the top
B. Dynamic programming
C. Back tracking
A. Dynamic programming
B. Backtracking
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D. Greedy method
7. In the case of sub problems share sub problems ,which method is suitable
A. greedy method
C. dynamic programming
8. The method which return different solutions from a single point ,which is
_________
A. greedy method
C. dynamic programming
A. Knapsack
C. Back tracking
D. Dynamic programming
A. greedy method
C. dynamic programming
A. greedy method
C. dynamic programming
A. greedy method
C. dynamic programming
4. The files x1,x2,x3 are 3 files of length 30,20,10 records each. What is the
optimal merge pattern value?
A. 110
B. 60
C. 90
D. 50
A. Greedy method
B. Dynamic programming
C. Knapsack method
A. /*
B. /
C. */
D. //
A. Space Complexity
B. Best Case
C. Time Complexity
D. Worst Case
A. Debugging
B. Combining
C. Profiling
D. Conqure
10. In Algorithm Specification the blockes are indicated with matching _______
A. Braces
B. Square Brackets
C. Parenthesis
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D. Slashes
A. BST
B. MST
C. Binary tree
D. Weighted Graph
A. Dynamic programming
B. Backtracking
D. Greedy method
3. ____________ is an algorithm design method that can be used when the solution
to a problem can be viewed as the result of a sequence of decisions
A. Dynamic programming
B. Backtracking
D. Greedy method
A. D.H. Lehmer
B. L. Baumert
C. R.J. Walker
D. S. Golomb
52
5. The term ________ refers to all state space search methods in which all children
of the –nodes are generated before any other live node can become the E-node.
A. Backtracking
6. A __________ is a round trip path along n edges of G that visits every vertex
once and returns to its starting position.
A. MST
B. TSP
C. Multistage Graph
D. Hamiltonian Cycle
A. Backtracking
B. Greedy
D. Dynamic programming
D. binary search algorithm is not efficient when the data elements are more
than 1000
D. Pointer array
A. Best case
B. Average case
C. Worst case
D. Null case
B. When Item is the last element in the middle of the array array
D. When Item is the last element in the array or is not there at all
B. Sometimes more complicated and than that of worst case some other
times simpler than that of
C. Much more simpler to analyze than worst case that of worst case
D. None or above
A. O(n)
B. O(n^2)
C. O(log n)
D. O(n log n)
A. O(n)
B. O(n^2)
C. O(log n)
D. O(n log n)
A. O(n)
B. O(n^2)
C. O(log n)
D. O(n log n)
A. O(n)
B. O(n^2)
C. O(log n)
D. O(n log n)
10. The time factor when determining the efficiency of algorithm is measured by
A. Counting microseconds
A. Bubble sort
B. Quick sort
C. Insertion sort
D. All of above
A. Sub algorithm
B. Polish notation
C. Recursion
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D. Traversal algorithm
A. No of inputs
B. Size o elements
D. Pivot element
A. O(n^2)
B. O(n+k)
C. O(nlogn)
D. O(n^3)
A. Large
B. Not known
C. Medium
D. Small
7. Quick sort is based on divide and conquer paradigm; we divide the problem
on base of pivot element and:
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D. None of above.
8. Dijkstra’s algorithm :
B. Has both greedy and Dynamic approach to find all shortest paths
C. Has greedy approach to compute single source shortest paths to all other
vertices
A. Greedy Technique
B. Divide-and-Conquer Technique
C. Both of above
A. It is massive
D. It is properly stated
A. Arrays
B. Linked lists
C. Time consuming
4. A linear list in which each node has pointers to point to the predecessor and
successors nodes is called as ..
5. A ……………….. is a linear list in which insertions and deletions are made to from
either end of the structure.
A. circular queue
B. random of queue
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C. priority
D. dequeue
D. any position
A. finding factorial
B. tower of Hanoi
A. queue
B. stack
C. tree
D. graph
A. linear
B. non linear
C. linked list
D. trees
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1. A binary tree whose every node has either zero or two children is called
D. None of above
2. When converting binary tree into extended binary tree, all the original nodes
in binary tree are
D. None of above
A. Sub algorithm
B. Recursion
C. Polish notation
D. Traversal algorithm
4. In a Heap tree
A. Values in a node is greater than every value in left sub tree and smaller
than right sub tree
A. a tree graph
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B. free tree
C. a tree
D. All of above
6. The in order traversal of tree will yield a sorted listing of elements of tree in
A. Binary trees
C. Heaps
D. None of above
D. None of these
A. PUSH
B. POP
C. Delete
D. None of these
A. Stack
B. Queue
C. Array
D. linked list
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10. The element which is inserted first will be removed last in the
A. Queue
B. Array
C. Linked list
D. None of these
A. Tree
B. String
C. Graph
D. Array
2. Which of the following operations accesses each record exactly once so that
certain items may be processed?
A. Inserting
B. Deleting
C. Traversing
D. Searching
3. Which of the following is also called first in first out FIFO system?
A. Tree
B. Stack
C. Queue
D. Graph
4. Which of the following is is also called last in first out LIFO system?
A. Queue
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B. Stack
C. Graph
D. Tree
A. Array
B. Linked list
C. Stack
D. Graph
A. Merging
B. Sorting
C. Traversing
D. Searching
7. Which of the following operations combined record into different sorted files
into a single sorted file?
A. Sorting
B. Merging
C. Searching
D. Inserting
8. Which of the following is a set of data values and associated operations that
are specified accurately, independent of any particular implementation?
A. Stack
B. Tree
D. Graph
A. Group item
B. Data item
C. Basic item
D. Elementary item
10. Which of the following is something that has certain attributes or properties
which may be assigned values?
A. Field
B. File
C. Records
D. Entity
11. Which of the following is the collection of records of the entities in a given
entity set?
A. Field
B. File
C. Records
D. Entity
12. The values in which field uniquely determine the record in a file
A. Primary key
B. Secondary key
C. Pointer
D. Key
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13. In which of the following length records file records may contain different
lengths?
A. Fixed
B. Primary
C. Variable
D. Entity
A. Structures
B. Variable
C. Data structures
D. Function
A. Boolean
B. Integer
C. Arrays
D. Character