Practice Worst Case Complexity (19.2.1) - Mergesort - Part A - Data Structures and Algorithms in Python
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Worst Case Complexity

Practice - Worst Case Complexity

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does the worst-case complexity of O(n²) mean for a sorting algorithm?

💡 Hint: Think about how time and length of data interact.

Question 2 Easy

What is the first step in the merge sort algorithm?

💡 Hint: What do we do before sorting?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the function of merge sort?

To reverse a list
To search for an element
To sort a list

💡 Hint: Consider what sorting means overall.

Question 2

True or False: Merge sort has a guaranteed worst-case performance of O(n log n).

True
False

💡 Hint: Think about the efficiency of the method itself.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a randomly shuffled array of integers, apply the merge sort algorithm to sort the array step by step. Document every split and merge operation.

💡 Hint: Keep track of the left and right sides as you merge them.

Challenge 2 Hard

Implement the merge sort algorithm in Python from scratch and evaluate its performance against a list of 10,000 random integers.

💡 Hint: Remember that merging is key – focus on how to efficiently combine the sorted halves.

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