CC104 - FT Quiz #1

What is the key strategy used by both Merge Sort and Quick Sort?

• Divide and conquer

• Dynamic programming

• Greedy method

• Backtracking

In Merge Sort, what is the primary purpose of dividing the list into two halves?

• To simplify the sorting process by working with smaller parts

• To find the middle element of the list

• To compare all elements directly with each other

• To remove duplicate values

Which of the following best describes the time complexity of Merge Sort?

• O(n log n)

• O(n^2)

• O(log n)

• O(n)

Which sorting technique requires a “pivot” element to split the list?

• Quick Sort

• Merge Sort

• Binary Search

• Bubble Sort

How does Binary Search work on a sorted list?

• By repeatedly dividing the search interval in half

• By scanning each element sequentially

• By calculating the sum of all elements

• By randomly selecting elements to compare

What is the best-case time complexity of Quick Sort?

• O(n log n)

• O(n^2)

• O(log n)

• O(1)

Why is Binary Search not suitable for unsorted lists?

• Because it relies on order to reduce search intervals

• Because it uses too much memory

• Because it sorts elements before searching

• Because it’s slower than linear search

What is the purpose of the partitioning step in Quick Sort?

• To separate elements smaller and larger than the pivot

• To split the list into two equal halves

• To merge two lists into one sorted list

• To find duplicate elements in the list

Which sorting algorithm would perform the best on an already sorted list?

• Merge Sort

• Quick Sort

• Binary Search

• Selection Sort

If Merge Sort takes O(n log n) time, what does the “log n” part represent?

• The recursive division of the list

• The number of comparisons made per element

• The maximum number of elements in the list

• The time taken to merge two halves