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Welcome to the Data Structures and Algorithms MCQs Page

Dive deep into the fascinating world of Data Structures and Algorithms with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Data Structures and Algorithms, a crucial aspect of UGC CBSE NET Exam. In this section, you will encounter a diverse range of MCQs that cover various aspects of Data Structures and Algorithms, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within UGC CBSE NET Exam.

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Check out the MCQs below to embark on an enriching journey through Data Structures and Algorithms. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of UGC CBSE NET Exam.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Data Structures and Algorithms. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Data Structures and Algorithms MCQs | Page 13 of 27

Explore more Topics under UGC CBSE NET Exam

Q121.
The decision tree classifier is a widely used technique for ...............

a.

Classification

b.

Association

c.

Partition

d.

Clustering

Discuss
Answer: (a).Classification
Q122.
Match the following :

(a) Dangling pointer    (i) Buffer replacement policy
(b) Page fault               (ii) Variable-length records
(c) List representation (iii) Object identifier
(d) Toss-immediate      (iv) Pointer-swizzling

Codes :
      (a)   (b)  (c)  (d)

a.

(iii)  (iv)  (ii)   (i)

b.

(iv)  (iii)  (ii)   (i)

c.

(iv)  (iii)  (i)   (ii)

d.

(iii)  (iv)  (i)   (ii)

Discuss
Answer: (a).(iii)  (iv)  (ii)   (i)
Q123.
The time complexity of recurrence relation

T(n) = T(n/3) + T(2n/3) + O(n)

is

a.

O(Ig n)

b.

O(n)

c.

O(n Ig n)

d.

O(n^2 )

Discuss
Answer: (c).O(n Ig n)
Q124.
The time complexity of an efficient algorithm to find the longest monotonically increasing subsequence of n numbers is

a.

O(n)

b.

O(n Ig n)

c.

O(n^2)

d.

None of the above

Discuss
Answer: (b).O(n Ig n)
Q125.
Given a binary search trees for a set of n=5 keys with the following probabilities. The expected optimal cost of the search is

a.

2.65

b.

2.70

c.

2.75

d.

2.80

Discuss
Answer: (c).2.75
Q126.
Given 0-1 knapsack problem and fractional knapsack problem and the following statements :

S1 : 0-1 knapsack is efficiently solved using Greedy algorithm.
S2 : Fractional knapsack is efficiently solved using Dynamic programming.

Which of the following is true ?

a.

S1 is correct and S2 is not correct

b.

Both S1 and S2 are correct

c.

Both S1 and S2 are not correct

d.

S1 is not correct and S2 is correct

Discuss
Answer: (c).Both S1 and S2 are not correct
Q127.
Consider the following sequence of operations :

(i) Pointer p1 is set to point at a new heap-dynamic variable.
(ii) Pointer p2 is assigned p1’s value.
(iii) The heap dynamic variable pointed to by p1 is explicitly de-allocated, but p2 is not changed by the operation.

This situation leads to which of the following :

a.

p1 becomes a dangling pointer

b.

p2 becomes a dangling pointer

c.

Both p1 and p2 are now dangling pointers

d.

Neither p1 nor p2 is now a dangling pointer

Discuss
Answer: (b).p2 becomes a dangling pointer
Q128.
Cyclometric complexity of a flow graph G with n vertices and e edges is

a.

V(G) = e+n-2

b.

V(G) = e-n+2

c.

V(G) = e+n+2

d.

V(G) = e-n-2

Discuss
Answer: (b).V(G) = e-n+2
Q129.
For a B-tree of height h and degree t, the total CPU time used to insert a node is

a.

O(h log t)

b.

O(t log h)

c.

O(t^2h)

d.

O(th)

Discuss
Answer: (d).O(th)
Q130.
The time complexity to build a heap with a list of n numbers is

a.

O(log n)

b.

O(n)

c.

O(n log n)

d.

O(n^2)

Discuss
Answer: (b).O(n)
Page 13 of 27

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