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2 cards from this section. Quick, good the night before a test.
What is asymptotic complexity?
Think about efficiency in the context of algorithms.
What is meant by worst-case analysis?
Consider scenarios where inputs are at their maximum size.
What does the term 'asymptotic complexity' refer to?
Focus on what happens as input sizes change.
True or False: O(n^2) algorithm is faster than O(n log n) for large datasets.
Think about the growth rates of these functions.
Given the two sorting algorithms, naive O(n^2) and efficient O(n log n), explain their efficiency differences when sorting a list of 10 million items.
Think about how input sizes increase the number of operations.
Design an experiment to benchmark sorting algorithms on dataset sizes of 1000, 10000, and 100000. What results do you expect to see between the naive and efficient algorithms?
Prepare to record time taken for each sorting method on those datasets.
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