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Algorithms in Java, Third Edition, Part 5: Graph Algorithms
By Robert Sedgewick
Publisher	: Addison Wesley
Pub Date	: July 15, 2003
ISBN	: 0-201-36121-3
Pages	: 528

		Copyright
		Preface
			Algorithms
			Scope
			Use in the Curriculum
			Algorithms of Practical Use
			Programming Language
			Acknowledgments
		Java Consultant's Preface
		Notes on Exercises
		Part V:  Graph Algorithms
			Chapter 17.  Graph Properties and Types
				Section 17.1.  Glossary
				Section 17.2.  Graph ADT
				Section 17.3.  Adjacency-Matrix Representation
				Section 17.4.  Adjacency-Lists Representation
				Section 17.5.  Variations, Extensions, and Costs
				Section 17.6.  Graph Generators
				Section 17.7.  Simple, Euler, and Hamilton Paths
				Section 17.8.  Graph-Processing Problems
			Chapter 18.  Graph Search
				Section 18.1.  Exploring a Maze
				Section 18.2.  Depth-First Search
				Section 18.3.  Graph-Search ADT Methods
				Section 18.4.  Properties of DFS Forests
				Section 18.5.  DFS Algorithms
				Section 18.6.  Separability and Biconnectivity
				Section 18.7.  Breadth-First Search
				Section 18.8.  Generalized Graph Search
				Section 18.9.  Analysis of Graph Algorithms
			Chapter 19.  Digraphs and DAGs
				Exercises
				Section 19.1.  Glossary and Rules of the Game
				Section 19.2.  Anatomy of DFS in Digraphs
				Section 19.3.  Reachability and Transitive Closure
				Section 19.4.  Equivalence Relations and Partial Orders
				Section 19.5.  DAGs
				Section 19.6.  Topological Sorting
				Section 19.7.  Reachability in DAGs
				Section 19.8.  Strong Components in Digraphs
				Section 19.9.  Transitive Closure Revisited
				Section 19.10.  Perspective
			Chapter 20.  Minimum Spanning Trees
				Exercises
				Section 20.1.  Representations
				Section 20.2.  Underlying Principles of MST Algorithms
				Section 20.3.  Prim's Algorithm and Priority-First Search
				Section 20.4.  Kruskal's Algorithm
				Section 20.5.  Boruvka's Algorithm
				Section 20.6.  Comparisons and Improvements
				Section 20.7.  Euclidean MST
			Chapter 21.  Shortest Paths
				Exercises
				Section 21.1.  Underlying Principles
				Section 21.2.  Dijkstra's Algorithm
				Section 21.3.  All-Pairs Shortest Paths
				Section 21.4.  Shortest Paths in Acyclic Networks
				Section 21.5.  Euclidean Networks
				Section 21.6.  Reduction
				Section 21.7.  Negative Weights
				Section 21.8.  Perspective
			Chapter 22.  Network Flow
				Section 22.1.  Flow Networks
				Section 22.2.  Augmenting-Path Maxflow Algorithms
				Section 22.3.  Preflow-Push Maxflow Algorithms
				Section 22.4.  Maxflow Reductions
				Section 22.5.  Mincost Flows
				Section 22.6.  Network Simplex Algorithm
				Section 22.7.  Mincost-Flow Reductions
				Section 22.8.  Perspective
		References for Part Five

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