Practice Time Complexity Of Merge (20.2.1) - Mergesort, analysis - Data Structures and Algorithms in Python
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Time Complexity of Merge

Practice - Time Complexity of Merge

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the time complexity of the merge function?

💡 Hint: Think about how many total comparisons you will make.

Question 2 Easy

Describe how two lists are merged in the merge sort.

💡 Hint: Focus on how comparisons are made between the two lists.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the time complexity of the merge process?

O(n)
O(n log n)
O(m+n)

💡 Hint: Look at the shape of the operations happening in merging.

Question 2

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

True
False

💡 Hint: Consider the elements from two lists that need to be merged.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given two sorted arrays A = [1,4,6] and B = [2,3,5], use the merge function to create a new sorted array.

💡 Hint: Compare the smallest elements from each list and continue until you finish merging both.

Challenge 2 Hard

If merging two lists A and B results in a final sorted array, explain the underlying steps in algorithmic terms.

💡 Hint: Think about how comparisons influence your next choices in merging.

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Reference links

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