Practice Measurement And Big-o Notation (8.2.1.3.2) - Undecidability and Introduction to Complexity Theory
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Measurement and Big-O Notation

Practice - Measurement and Big-O Notation

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does O(1) time complexity represent?

💡 Hint: Think about operations like accessing elements.

Question 2 Easy

Which time complexity corresponds to a linear search in an array?

💡 Hint: Consider how many checks you need to make.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is Big-O notation primarily used for?

To evaluate memory usage
To measure execution time
To describe algorithm efficiency

💡 Hint: Think about what it measures in algorithms.

Question 2

True or False: O(log n) is faster than O(n).

True
False

💡 Hint: Consider the implications of input size increase.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Devise a new sorting algorithm and analyze its Big-O performance. What characteristics will make it practical for larger datasets?

💡 Hint: Think about how you might optimize an existing approach.

Challenge 2 Hard

Evaluate an algorithm that implements O(3^n). Discuss its feasibility and environments where it might be used despite its inefficiency.

💡 Hint: Examine smaller input sizes for better insights.

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Reference links

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