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5 cards from this section. Quick, good the night before a test.
What is the purpose of Big O notation?
Think about the relationship between input size and algorithm performance.
What is an example of a greedy algorithm?
Consider a problem where you want to minimize the number of coins.
What does Big O notation measure?
Think about what aspect of algorithm performance you're analyzing.
True or False: Greedy algorithms always guarantee optimal solutions.
Consider scenarios where choosing locally optimal results fails.
You are given a list of tasks with deadlines and profits. Describe how you would apply a greedy algorithm to maximize profit while respecting deadlines.
Arrange and prioritize based on profit and timing.
In the context of the Fibonacci sequence, illustrate how dynamic programming optimizes performance compared to a naive recursive approach.
Visualize overlapping calculations in the naive method.
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