Comparing Algorithms
Explore how to effectively compare algorithms by focusing on execution time and space requirements. Learn the challenges of experimental evaluation, the role of analytical methods, and how to apply worst-case, best-case, and average-case analyses. Gain skills in calculating primitive operations to measure time complexity and understand constant-time algorithms through Java examples.
Introduction
There are typically several different algorithms to solve a given computational problem. It is natural, then, to compare these alternatives. But how do we know if algorithm A is better than algorithm B?
Important criteria: Time and space
One important factor that determines the “quality” of an algorithm is the amount of time it takes to solve a given problem. If algorithm A takes less time to solve the same problem than algorithm B, then algorithm A is considered better.
Another important factor in comparing two algorithms is the amount of memory required to solve a given problem. The algorithm that requires less memory is ...