Practice Storage Limitations - 20.5.1 | 20. Mergesort, analysis | Data Structures and Algorithms in Python
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define merge sort in your own words.

πŸ’‘ Hint: Think about the steps involved in sorting.

Question 2

Easy

What is the time complexity of merge sort?

πŸ’‘ Hint: Consider how the algorithm divides the input list.

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 time complexity of merge sort?

  • O(n)
  • O(n log n)
  • O(log n^2)

πŸ’‘ Hint: Think about how many times the list can be divided.

Question 2

True or False: Merge sort can perform in-place sorting.

  • True
  • False

πŸ’‘ Hint: Consider how merging is performed.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset of 10,000 elements, explain how you would justify using merge sort over insertion sort in a performance-critical application.

πŸ’‘ Hint: Consider the size of the dataset and the performance impact.

Question 2

Implement a merge function to combine two sorted arrays without using extra space. Describe the challenges involved.

πŸ’‘ Hint: Think about how to move elements around without exceeding array bounds.

Challenge and get performance evaluation