Practice - Table for Input Size vs Time Complexity
Practice Questions
Test your understanding with targeted questions
What does algorithm efficiency refer to?
💡 Hint: Think about time taken to complete the function.
What is big O notation used for?
💡 Hint: It's a shorthand for expressing growth rate.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What type of complexity does O(n) represent?
💡 Hint: Consider what linear means in a real-world context.
True or False: Worst-case efficiency is the same as average-case efficiency.
💡 Hint: Think of which scenario is more critical for performance.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Consider a scenario where you are tasked with sorting 100,000 entries in a database. Which sorting algorithm would you choose and why? Include considerations for both time complexity and practicality.
💡 Hint: Think about how long it would take to run the sorting task.
Given an algorithm with exponential time complexity, discuss the practical limits on input size. How would you approach handling a problem that grows exponentially?
💡 Hint: What examples can you identify that tend to grow exponentially, and how do they compare to others?
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Reference links
Supplementary resources to enhance your learning experience.