1.5.1 - Asymptotic Complexity
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Practice Questions
Test your understanding with targeted questions
What is Big O notation?
💡 Hint: Think of it as a way to categorize how algorithms behave as input sizes increase.
Explain the significance of asymptotic complexity.
💡 Hint: Focus on the importance of comparing different algorithms.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does Big O notation represent?
💡 Hint: Look at how we express the efficiency of algorithms.
Is Linear Search O(n) better, worse, or equivalent to Binary Search O(log n) for large datasets?
💡 Hint: Consider their respective time complexities.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Given an algorithm with a complexity of O(n^3) and another of O(n), design a test to showcase the effects of input size on performance, providing graphs of their running times.
💡 Hint: What conditions can help demonstrate the scaling effects?
You are tasked with processing sales data for an eCommerce site. Choose between a quicksort algorithm O(n log n) and a bubble sort O(n^2). Discuss implications of each choice based on expected data size and performance.
💡 Hint: How do both algorithms perform as input sizes increase?
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