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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the worst-case time complexity of the merge sort algorithm?
💡 Hint: Consider how many times the list is divided.
Question 2
Easy
How does merge sort utilize the divide-and-conquer strategy?
💡 Hint: Think about the steps involved in the sorting process.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary benefit of using merge sort over simpler sorting algorithms?
- Faster for small datasets
- In-Place sorting
- Better efficiency for large datasets
💡 Hint: Think about performance with larger data.
Question 2
True or False: Merge sort can sort a list that is already sorted in O(n) time.
- True
- False
💡 Hint: Consider the algorithm's mechanics.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given the following unsorted list: [38, 27, 43, 3, 9, 82, 10], demonstrate how the merge sort would work step-by-step.
💡 Hint: Start by breaking the list down completely.
Question 2
Implement the merge function in Python that takes two sorted lists and returns a new sorted list.
💡 Hint: Think about how to append elements from both lists based on comparison.
Challenge and get performance evaluation