May 2019
Beginner to intermediate
800 pages
21h 59m
English
Content preview from Essential Algorithms, 2nd Edition
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CHAPTER 17Complexity Theory
An algorithm's performance is always important when you try to solve a problem. An algorithm won't do you much good if it takes too long or requires too much memory or other resources to actually run on a computer.
Computational complexity theory, or just complexity theory, is the study of the difficulty of computational problems. Rather than focusing on specific algorithms, complexity theory focuses on problems.
For example, the mergesort algorithm described in Chapter 6 can sort a list of N numbers in O(N log N) time. Complexity theory asks what you can learn about the task of sorting in general, not what you can learn about a specific algorithm. It turns out that you can show that any sorting algorithm that sorts by using comparisons must use at least N × log(N) time in the worst case.
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