Quiz for:
Understanding Sorting Algorithms and Efficiency

Question 1

Which algorithm can be improved to O(n) time complexity in best-case scenarios when the list is sorted?

Question 2

Which sorting algorithm works by stepping through the list to be sorted, comparing adjacent items, and swapping them if they are in the wrong order?

Question 3

Which sorting algorithm repeatedly finds the minimum element from the unsorted part and puts it at the beginning?

Question 4

What is the Divide and Conquer strategy in problem-solving?

Question 5

What is the main goal of understanding algorithms in programming?

Question 6

Which algorithm is generally more efficient for larger lists compared to O(n^2) sorting algorithms?

Question 7

What does the Big O notation describe about algorithms?

Question 8

What is the time complexity of Selection Sort?

Question 9

Why is understanding the efficiency of algorithms important in programming?

Question 10

What is Recursion in algorithms?

Question 11

What is the time complexity of Merge Sort for sorting a list of n elements?

Question 12

What concept involves solving a large problem by breaking it into smaller sub-problems and then combining the answers?

Question 13

What type of visualization helps understand how algorithms sort data step-by-step?

Question 14

How does Merge Sort divide the input array to sort it?

Question 15

What is the time complexity of Bubble Sort in best-case scenarios when the list is already sorted?