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4 cards from this section. Quick, good the night before a test.
Define input size in relation to algorithms.
Think about how we quantify the data in an algorithm.
What does worst-case analysis help us understand?
Consider scenarios where inputs might be challenging.
What does 'input size' refer to in algorithm analysis?
Focus on what metrics influence algorithm performance.
True or False: The average case analysis is always more informative than the worst-case analysis.
Think about when you would want maximum performance assurance.
In an algorithm that sorts an array, what is the worst-case scenario when determining the time complexity? Illustrate this with an example.
Think of sorting methods and how they operate on data.
Discuss how changing the representation of graphs (adjacency matrix vs. adjacency list) affects the complexity of operations and the definition of input sizes.
Visualize how graph data structures differ and their relationship with operations.
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