Practice Recursion Depth And Performance (21.3.1) - Quicksort - Data Structures and Algorithms in Python
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Recursion Depth and Performance

Practice - Recursion Depth and Performance

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Practice Questions

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Question 1 Easy

What does merge sort require extra space for?

💡 Hint: Think about what happens during the merging process.

Question 2 Easy

What is a pivot in quicksort?

💡 Hint: Recall how elements are sorted relative to this chosen value.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

Which sorting algorithm requires additional space for merging?

Merge Sort
Quicksort
Bubble Sort

💡 Hint: Consider the steps in each sorting process.

Question 2

True or False: Quicksort always has a time complexity of O(n log n).

True
False

💡 Hint: Think about the effect of pivot selection.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a quicksort algorithm that avoids worst-case performance by implementing a better pivot strategy.

💡 Hint: Think about how average values can help stabilize the partition balance.

Challenge 2 Hard

Explain how recursion depth can be optimized in Python for large lists when using quicksort.

💡 Hint: Remember, Python has a default recursion limit which may not fit all sorting scenarios.

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Reference links

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