算法技术手册(影印版)
算法技术手册(影印版)
George T. Heineman, Gary Pollice, Stanley Selkow
出版时间:2009年04月
页数:343
创造稳定的软件需要有效的算法,但是程序设计者们很少能在问题出现之前就想到。《算法技术手册》描述了现有的可以解决多种问题的算法,并且能够帮助你根据需求选择并实现正确的算法——只需要一定的数学知识即可理解并分析算法执行。

相对于理论来说,本书更注重实际运用,书中提供了多种程序语言中可用的有效代码解决方案,可轻而易举地适合一个特定的项目。有了这本书,你可以:

* 解决特定编码问题或改进现有解决方案的执行展开全部内容介绍
  1. Preface
  2. Part I.
  3. 1. Algorithms Matter
  4. Understand the Problem
  5. Experiment if Necessary
  6. Algorithms to the Rescue
  7. Side Story
  8. The Moral of the Story
  9. References
  10. 2. The Mathematics of Algorithms
  11. Size of a Problem Instance
  12. Rate of Growth of Functions
  13. Analysis in the Best, Average, and Worst Cases
  14. Performance Families
  15. Mix of Operations
  16. Benchmark Operations
  17. One Final Point
  18. References
  19. 3. Patterns and Domains
  20. Patterns: A Communication Language
  21. Algorithm Pattern Format
  22. Pseudocode Pattern Format
  23. Design Format
  24. Empirical Evaluation Format
  25. Domains and Algorithms
  26. Floating-Point Computations
  27. Manual Memory Allocation
  28. Choosing a Programming Language
  29. References
  30. Part II.
  31. 4. Sorting Algorithms
  32. Overview
  33. Insertion Sort
  34. Median Sort
  35. Quicksort
  36. Selection Sort
  37. Heap Sort
  38. Counting Sort
  39. Bucket Sort
  40. Criteria for Choosing a Sorting Algorithm
  41. References
  42. 5. Searching
  43. Overview
  44. Sequential Search
  45. Binary Search
  46. Hash-based Search
  47. Binary Tree Search
  48. 6. Graph Algorithms
  49. Overview
  50. Depth-First Search
  51. Breadth-First Search
  52. Single-Source Shortest Path
  53. All Pairs Shortest Path
  54. Minimum Spanning Tree Algorithms
  55. References
  56. 7. Path Finding in AI
  57. Overview
  58. Depth-First Search
  59. Breadth-First Search
  60. A*Search
  61. Comparison
  62. Minimax
  63. NegMax
  64. AlphaBeta
  65. References
  66. 8. Network Flow Algorithms
  67. Overview
  68. Maximum Flow
  69. Bipartite Matching
  70. Reflections on Augmenting Paths
  71. Minimum Cost Flow
  72. Transshipment
  73. Transportation
  74. Assignment
  75. Linear Programming
  76. References
  77. 9. Computational Geometry
  78. Overview
  79. Convex Hull Scan
  80. LineSweep
  81. Nearest Neighbor Queries
  82. Range Queries
  83. References
  84. Part III.
  85. 10. When All Else Fails
  86. Variations on a Theme
  87. Approximation Algorithms
  88. Offline Algorithms
  89. Parallel Algorithms
  90. Randomized Algorithms
  91. Algorithms That Can Be Wrong, but with Diminishing Probability
  92. References
  93. 11. Epilogue
  94. Overview
  95. Principle: Know Your Data
  96. Principle: Decompose the Problem into Smaller Problems
  97. Principle: Choose the Right Data Structure
  98. Principle: Add Storage to Increase Performance
  99. Principle: If No Solution Is Evident, Construct a Search
  100. Principle: If No Solution Is Evident, Reduce Your Problem to
  101. Another Problem That Has a Solution
  102. Principle: Writing Algorithms Is Hard—Testing Algorithms Is
  103. Harder
  104. Part IV.
  105. Appendix: Benchmarking
  106. Index
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定价:58.00元
书号:978-7-5641-1632-3
出版社:东南大学出版社