Practice Worst-case Estimates (5.3.2) - Design and Analysis of Algorithms

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6 sample questions

Question 1.
Define algorithm efficiency in your own words.
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Think of both speed and memory use.
Question 2.
What does the term 'worst-case analysis' refer to?
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Focus on time during worst scenarios.
3Question 3.
What does worst-case analysis refer to in algorithm design?
- Best possible input scenario
- Average performance prediction
- The maximum time required for the worst input case
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Think about scenarios where the algorithm struggles.
4Question 4.
True or False: In general, O(n log n) is faster than O(n²).
- True
- False
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Consider how each algorithm scales with larger datasets.
Question 5.
Given an input size of 1,000, explain how many operations an O(n²) algorithm would need and the implications.
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Square the input size.
Question 6.
If an algorithm runs in O(2^n) time, evaluate its practicality for n=20 and explain.
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Calculate the exponential growth for larger inputs.

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