Merge Sort is based on which algorithmic paradigm?
A
Greedy B
Dynamic Programming C
Divide and Conquer D
Backtracking
Analysis & Theory
Merge Sort splits the array into halves, sorts them recursively, and merges the results (Divide and Conquer).
What is the worst-case time complexity of Merge Sort?
A
O(n) B
O(n log n) C
O(n^2) D
O(log n)
Analysis & Theory
Merge Sort always runs in O(n log n) time in best, average, and worst cases.
Which of the following statements about Merge Sort is TRUE?
A
It is an in-place sorting algorithm B
It is a stable sort C
It is adaptive D
It uses less memory than Quick Sort
Analysis & Theory
Merge Sort is stable because equal elements preserve their relative order after merging.
Merge Sort is preferred over Quick Sort for which of the following cases?
A
Large datasets in memory B
Small datasets C
Linked lists D
Arrays with many duplicates
Analysis & Theory
Merge Sort is efficient for linked lists because it doesn’t require random access.
What is the auxiliary space complexity of Merge Sort for arrays?
A
O(1) B
O(log n) C
O(n) D
O(n log n)
Analysis & Theory
Merge Sort requires O(n) extra space to store the merged output.
Which step in Merge Sort combines two sorted halves?
A
Partitioning B
Merging C
Splitting D
Selection
Analysis & Theory
After recursive sorting, Merge Sort merges two sorted subarrays.
Which of these sorting algorithms has the same time complexity as Merge Sort in all cases?
A
Heap Sort B
Bubble Sort C
Insertion Sort D
Selection Sort
Analysis & Theory
Heap Sort also has O(n log n) worst-case time complexity.
Is Merge Sort a comparison-based sorting algorithm?
A
Yes B
No
Analysis & Theory
Merge Sort compares elements while merging.
Merge Sort divides the array until the size becomes:
A
n/2 B
1 C
log n D
0
Analysis & Theory
It divides recursively until single-element subarrays are reached.
Which of these is a disadvantage of Merge Sort?
A
It is unstable B
It is slow on linked lists C
It requires extra space D
It has quadratic time complexity
Analysis & Theory
Merge Sort requires O(n) auxiliary space.