Practice Definition (8.2.1.2.1) - Undecidability and Introduction to Complexity Theory
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Definition

Practice - Definition - 8.2.1.2.1

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Practice Questions

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Question 1 Easy

What does time complexity measure?

💡 Hint: Think about the relation between the input size and the processing time.

Question 2 Easy

Give an example of an algorithm with O(1) complexity.

💡 Hint: What happens when you know the index directly?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does time complexity help us understand?

The memory usage of an algorithm
The running time of an algorithm
The correctness of an algorithm

💡 Hint: Think about what aspect of an algorithm you want to measure during its execution.

Question 2

True or False: Big-O notation describes the lower bound of an algorithm's growth rate.

True
False

💡 Hint: Consider the direction Big-O describes.

1 more question available

Challenge Problems

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Challenge 1 Hard

Design an algorithm that sorts a list of n numbers and analyze its time and space complexity.

💡 Hint: Think about the relationship between sorting methods and their complexities.

Challenge 2 Hard

Describe a scenario where an O(n^2) algorithm might still be preferable to an O(log n) one.

💡 Hint: Consider the size of the input that is being dealt with.

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