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3 cards from this section. Quick, good the night before a test.
What does time complexity measure?
Think about how increases in input size affect the running time.
Define a basic operation in the context of algorithms.
Identify simple actions an algorithm performs.
What does time complexity primarily focus on?
Consider what 'complexity' stands for in algorithm analysis.
True or False: Time complexity is not affected by the size of the input.
Reflect on how algorithms behave differently with different data sizes.
You have two sorting algorithms: one with time complexity O(n^2) and another with O(n log n). Evaluate their performance with an input size of 100,000. How do the runtimes compare?
Calculations involve comparing n² with n log n as n increases.
Identify a real-world scenario where you would prefer a logarithmic algorithm over a quadratic one, and justify your choice.
Consider scenarios involving large datasets and the required speed of response.
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