Explore topic-wise MCQs in Data Structures and Algorithms.

This section includes 13 Mcqs, each offering curated multiple-choice questions to sharpen your Data Structures and Algorithms knowledge and support exam preparation. Choose a topic below to get started.

1.

What is the value stored in LIS[5] after the following program is executed?

A. 2
B. 3
C. 4
D. 5View Answer
Answer» D. 5View Answer
Discussion
2.

What is the space complexity of the following dynamic programming implementation used to find the length of the longest increasing subsequence?

A. O(1)
B. O(n)
C. O(n2)
D. O(nlogn)View Answer
Answer» C. O(n2)
Discussion
3.

What is the time complexity of the following dynamic programming implementation used to find the length of the longest increasing subsequence?

A. O(1)
B. O(n)
C. O(n2)
D. O(nlogn)View Answer
Answer» D. O(nlogn)View Answer
Discussion
4.

Complete the following dynamic programming implementation of the longest increasing subsequence problem:

A. tmp_max = LIS[j]
B. LIS[i] = LIS[j]
C. LIS[j] = tmp_max
D. tmp_max = LIS[i] View Answer
Answer» B. LIS[i] = LIS[j]
Discussion
5.

The number of increasing subsequences with the longest length for the given sequence are: {10, 9, 8, 7, 6, 5}

A. 3
B. 4
C. 5
D. 6
Answer» E.
Discussion
6.

Find the length of the longest increasing subsequence for the given sequence: {-10, 24, -9, 35, -21, 55, -41, 76, 84}

A. 5
B. 4
C. 3
D. 6
Answer» E.
Discussion
7.

Find the longest increasing subsequence for the given sequence: {10, -10, 12, 9, 10, 15, 13, 14}

A. {10, 12, 15}
B. {10, 12, 13, 14}
C. {-10, 12, 13, 14}
D. {-10, 9, 10, 13, 14}
Answer» E.
Discussion
8.

The longest increasing subsequence problem is a problem to find the length of a subsequence from a sequence of array elements such that the subsequence is sorted in increasing order and it’s length is maximum. This problem can be solved using __________

A. Recursion
B. Dynamic programming
C. Brute force
D. Recursion, Dynamic programming, Brute force
Answer» E.
Discussion
9.

WHAT_IS_THE_TIME_COMPLEXITY_OF_THE_ABOVE_DYNAMIC_PROGRAMMING_IMPLEMENTATION_USED_TO_FIND_THE_LENGTH_OF_THE_LONGEST_INCREASING_SUBSEQUENCE??$

A. O(1)
B. O(n)
C. O(n<sup>2</sup>)
D. O(nlogn)
Answer» C. O(n<sup>2</sup>)
Discussion
10.

What is the space complexity of the ABOVE dynamic programming implementation used to find the length of the longest increasing subsequence?$

A. O(1)
B. O(n)
C. O(n<sup>2</sup>)
D. O(nlogn)
Answer» E.
Discussion
11.

In the brute force implementation to find the longest increasing subsequence, all the subsequences of a given sequence are found. All the increasing subsequences are then selected and the length of the longest subsequence is found. What is the time complexity of this brute force implementation?

A. O(n)
B. O(n<sup>2</sup>)
C. O(n!)
D. O(2<sup>n</sup>)
Answer» E.
Discussion
12.

For any given sequence, there will ALWAYS be a unique increasing subsequence with the longest length.

A. True
B. False
Answer» C.
Discussion
13.

The longest increasing subsequence problem is a problem to find the length of a subsequence from a sequence of array elements such that the subsequence is sorted in increasing order and it’s length is maximum. This problem can be solved using __________

A. Recursion
B. Dynamic programming
C. Brute force
D. All of the mentioned
Answer» E.
Discussion