Dynamic Programming in Data Structures MCQ question and answer with solution

A. Recursion with memoization.

B. Greedy approach.

C. Divide and conquer.

D. Overlapping subproblems and optimal substructure.

A. Binary Search

B. Depth-First Search

C. Longest Common Subsequence

D. Quick Sort

A. It makes the code simpler.

B. It reduces the time complexity by storing results of subproblems.

C. It uses more memory.

D. It makes the code simpler.

A. Using a stack to manage function calls.

B. A method for dividing problems.

C. Storing intermediate results to avoid redundant calculations.

D. A technique to speed up sorting.

A. Depth-First Search

B. Binary Search

C. Quick Sort

D. Knapsack Problem

A. The solution to a problem can be constructed from the solutions to its subproblems.

B. The problem can be solved by dividing it into smaller problems.

C. The problem can be solved using greedy methods.

D. The problem can be solved using brute force.

A. O(log n)

B. O(n²)

C. O(n)

D. O(2ⁿ)

A. Greedy algorithms solve subproblems optimally.

B. DP is faster and uses less memory.

C. DP considers all possible solutions and builds up to the optimal solution.

D. Greedy algorithms always use recursion.

A. Sorting and searching.

B. Bottom-up or top-down approaches.

C. Direct computation.

D. Sorting and searching.

A. A method for optimizing search.

B. A global variable used in recursion.

C. A representation of a subproblem solution.

D. A function that directly solves the problem.