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3 cards from this section. Quick, good the night before a test.
What is the primary focus of time measurement in algorithm analysis?
Think about why time is more fixed compared to space.
What does a step in an algorithm usually represent?
Recall the types of operations we discussed.
What does O(n²) indicate in algorithm complexity?
Consider how the comparisons increase.
True or False: Time complexity analyzes the time taken by an algorithm to run relative to its input size.
Think about how algorithms handle larger inputs.
Analyze the effects of increasing data size on algorithm performance. Explain how algorithm choice impacts usability when sorting large datasets.
Think about dataset examples like millions of users.
Demonstrate using pseudocode how you would implement a sorting function that adapts to input size, aiming for the best time complexity.
Consider edge cases for small vs. large inputs.
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