CC104 - Final Exam

What is the primary purpose of the Merge Sort algorithm?

• To find the minimum element in an array

• To divide an array into smaller sub-arrays and then merge them

• To sort an array using comparisons

• To create a binary search tree

Which of the following is the best-case time complexity of Merge Sort?

• O(n)

• O(n log n)

• O(n^2)

• O(log n)

Which of the following is true about Quick Sort?

• It always performs better than Merge Sort

• It is a divide-and-conquer algorithm

• It requires more memory than Merge Sort

• It cannot be implemented recursively

The time complexity of Quick Sort in the worst case is:

• O(n log n)

• O(n)

• O(n^2)

• O(log n)

What is the basic idea behind the Binary Search algorithm?

• Check all elements one by one

• Divide the array into two halves and check the middle element

• Sort the array and then search for an element

• Search in the entire array sequentially

Which of the following is the time complexity of Binary Search?

• O(n)

• O(n log n)

• O(log n)

• O(n^2)

What is the space complexity of Merge Sort?

• O(1)

• O(log n)

• O(n)

• O(n^2)

Which algorithm is known for its "divide-and-conquer" approach?

• Merge Sort

• Quick Sort

• Binary Search

• All of the above

In Merge Sort, how is the merge operation typically performed?

• By dividing the array into two equal halves and merging them

• By recursively dividing the array and combining it in sorted order

• By sorting the left half and adding the right half at the end

• By sorting the entire array in one step

In Quick Sort, what happens after partitioning the array around the pivot?

• The pivot is placed at its correct position, and the subarrays are recursively sorted

• The array is sorted in descending order

• The array is divided into two parts, but not sorted

• The entire array is sorted in one go