内容简介

思路特别、平易近人的算法设计教材第二版，作者对常见陷阱做了指导，增加了机器学习算法并循序渐进提升学生对算法的全局认识，独特清晰地解释循环不变式等复杂主题，帮助学生进行抽象思维，为他们创造自己的创新方法解决问题做好准备。
 

章节内容

Preface; Introduction; Part I. Iterative Algorithms and Loop Invariants: 1. Iterative algorithms:measures of progress and loop invariants; 2. Examples using more-of-the-input loop invariant; 3.Abstract data types; 4. Narrowing the search space: binary search; 5. Iterative sorting algorithms;

6. Euclid's GCD algorithm; 7. The loop invariant for lower bounds; 8. Key concepts summary:loop invariants and iterative algorithms; 9. Additional exercises: Part I; 10. Partial solutions to additional exercises: Part I; Part II. Recursion: 11. Abstractions, techniques, and theory; 12.Some simple examples of recursive algorithms; 13. Recursion on trees; 14. Recursive images;15. Parsing with context-free grammars; 16. Key concepts summary: recursion; 17. Additional exercises: Part II; 18. Partial solutions to additional exercises: Part II; Part III. Optimization Problems: 19. Definition of optimization problems;
20. Graph search algorithms; 21. Network flows and linear programming; 22. Greedy algorithms; 23. Recursive backtracking; 24. Dynamic programming algorithms; 25. Examples of dynamic programming; 26. Reductions and NP-completeness; 27. Randomized algorithms; 28. Key concepts summary: greedy algorithms and dynamic programmings; 29. Additional exercises: Part III; 30. Partial solutions to additional exercises: Part III; Part IV. Additional Topics: 31. Existential and universal quantifiers; 32. Time complexity; 33. Logarithms and exponentials; 34. Asymptotic growth; 35. Adding-made-easy

approximations; 36. Recurrence relations; 37. A formal proof of correctness; 38. Additional exercises: Part IV; 39. Partial solutions to additional exercises: Part IV; Exercise Solutions;Conclusion; Index.
 

学术水平：undergraduate students

读者群：computer science