Algorithms play the central role in both the science and practice of computing. Recognition of this fact has led to the appearance of a considerable number of textbooks on the subject. By and large, they follow one of two alternatives in presenting algorithms. One classifies algorithms according to a problem type. Such a book would have separate chapters on algorithms for sorting, searching, graphs, and so on. The advantage of this approach is that it allows an immediate comparison of, say, the efficiency of different algorithms for the same problem. The drawback of this approach is that it emphasizes problem types at the expense of algorithm design techniques.

1. Introduction
2. Fundamentals of the Analysis of Algorithm Efficiency
3. Brute Force
4. Divide-and-Conquer
5. Decrease-and-Conquer
6. Transform-and-Conquer
7. Space and Time Tradeoffs
8. Dynamic Programming
9. Greedy Technique
10. Iterative Improvement

Etc.