Practice Limitations Of Merge Sort (20.5) - Mergesort, analysis - Data Structures and Algorithms in Python
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Limitations of Merge Sort

Practice - Limitations of Merge Sort

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the time complexity of Merge Sort?

💡 Hint: Recall the algorithm's performance characteristics.

Question 2 Easy

What is one advantage of Merge Sort?

💡 Hint: Think about stability in sorting.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary space concern with Merge Sort?

It requires a binary search tree.
It needs O(n) extra space for merging.
It has no space concerns.
It needs to store all elements in the same array.

💡 Hint: Think about how the merging process works.

Question 2

True or False: Merge Sort is an in-place sorting algorithm.

True
False

💡 Hint: Consider if the algorithm modifies the original array without extra space.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given an array of 1,000,000 integers, would Merge Sort still be efficient if implemented recursively? Discuss the implications of memory limits and recursion depth.

💡 Hint: Consider the depth of recursion and the space used.

Challenge 2 Hard

Evaluate a scenario where using Merge Sort is warranted despite its limitations. Describe the conditions under which it would be the best choice.

💡 Hint: Consider where data integrity is essential for the sorted outcomes.

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Reference links

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