What are some common algorithm analysis techniques?
Common techniques include Big O notation, space complexity analysis, and empirical analysis.
Can you explain Big O notation?
Big O notation describes the upper limit of an algorithm's running time or space requirements in relation to input size.
What is space complexity analysis?
Space complexity analysis measures the amount of working storage an algorithm needs as a function of the input size.
How do I perform empirical analysis?
Empirical analysis involves running the algorithm with various input sizes and measuring the actual time or space used.
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