Practice Storage Limitations (20.5.1) - Mergesort, analysis - Data Structures and Algorithms in Python
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Storage Limitations

Practice - Storage Limitations

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define merge sort in your own words.

💡 Hint: Think about the steps involved in sorting.

Question 2 Easy

What is the time complexity of merge sort?

💡 Hint: Consider how the algorithm divides the input list.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the time complexity of merge sort?

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

💡 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

💡 Hint: Consider how merging is performed.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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

💡 Hint: Consider the size of the dataset and the performance impact.

Challenge 2 Hard

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

💡 Hint: Think about how to move elements around without exceeding array bounds.

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Reference links

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