Preface to the Second Edition1. Thinking in Algorithms Understand the Problem Naive Solution Intelligent Approaches Summary References2. The Mathematics of Algorithms Size of a Problem Instance Rate of Growth of Functions Analysis in the Best, Average, and Worst Cases Performance Families Benchmark Operations References3. Algorithm Building Blocks Algorithm Template Format Pseudocode Template Format Empirical Evaluation Format Floating-Point Computation Example Algorithm Common Approaches References4. Sorting Algorithms Transposition Sorting Selection Sort Heap Sort Partition-Based Sorting Sorting without Comparisons Bucket Sort Sorting with Extra Storage String Benchmark Results Analysis Techniques References5. Searching Sequential Search Binary Search Hash-Based Search Bloom Filter Binary Search Tree References6. Graph Algorithms Graphs Depth-First Search Breadth-First Search Single-Source Shortest Path Dijkstra's Algorithm for Dense Graphs Comparing Single-Source Shortest-Path Options All-Pairs Shortest Path Minimum Spanning Tree Algorithms Final Thoughts on Graphs References7. Path Finding in AI Game Trees Path-Finding Concepts Minimax NegMax AlphaBeta Search Trees Depth-First Search Breadth-First Search A'Search Comparing Search-Tree Algorithms References8. Network Flow Algorithms Network Flow Maximum Flow Bipartite Matching Reflections on Augmenting Paths Minimum Cost Flow Transshipment Transportation Assignment Linear Programming References9. Computational Ge0metry Classifying Problems Convex Hull Convex Hull Scan Computing Line-Segment Intersections LineSweep Voronoi Diagram References10. Spatial Tree Structures Nearest Neighbor Queries Range Queries Intersection Queries Spatial Tree Structures Nearest Neighbor Queries Range Query Quadtrees R-Trees References11. Emerging Algorithm Categories Variations on a Theme Approximation Algorithms Parallel Algorithms Probabilistic Algorithms References12. Epilogue: Principles of Algorithms Know Your Data Decompose a Problem into Smaller Problems Choose the Right Data Structure Make the Space versus Time Trade-Off Construct a Search Reduce Your Problem to Another Problem Writing Algorithms Is Hard-Testing Algorithms Is Harder Accept Approximate Solutions When Possible Add Parallelism to Increase PerformanceA. BenchmarkingIndex