Once again, Robert Sedgewick provides a current and comprehensive introduction to important algorithms. The focus this time is on graph algorithms, which are increasingly critical for a wide range of applications, such as network connectivity, circuit design, scheduling, transaction processing, and resource allocation. In this book, Sedgewick offers the same successful blend of theory and practice that has made his work popular with programmers for many years. Christopher van Wyk and Sedgewick have developed concise new C++ implementations that both express the methods in a natural and direct manner and also can be used in real applications.

Algorithms in C++, Third Edition, Part 5: Graph Algorithms is the second book in Sedgewick's thoroughly revised and rewritten series. The first book, Parts 1-4, addresses fundamental algorithms, data structures, sorting, and searching. A forthcoming third book will focus on strings, geometry, and a range of advanced algorithms. Each book's expanded coverage features new algorithms and implementations, enhanced descriptions and diagrams, and a wealth of new exercises for polishing skills. A focus on abstract data types makes the programs more broadly useful and relevant for the modern object-oriented programming environment.

Coverage includes:

• A complete overview of graph properties and types
• Diagraphs and DAGs
• Minimum spanning trees
• Shortest paths
• Network flows
• Diagrams, sample C++ code, and detailed algorithm descriptions

The Web site for this book (http://www.cs.princeton.edu/~rs/) provides additional source code for programmers along with a wide range of academic support materials for educators.

A landmark revision, Algorithms in C++, Third Edition, Part 5 provides a complete tool set for programmers to implement, debug, and use graph algorithms across a wide range of computer applications.

Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University. He is a Director of Adobe Systems and has served on the research staffs at Xerox PARC, IDA, and INRIA. He earned his Ph.D from Stanford University under Donald E. Knuth.

17. Graph Properties and Types.

Glossary.

Graph ADT.

Adjacency-Matrix Representation.

Adjacency-Lists Representation.

Variations, Extensions, and Costs.

Graph Generators.

Simple, Euler, and Hamilton Paths.

Graph-Processing Problems.

Exploring a Maze.

Depth-First Search.

Graph-Search ADT Functions.

Properties of DFS Forests.

DFS Algorithms.

Separability and Biconnectivity.

Breadth-First Search.

Generalized Graph Search.

Analysis of Graph Algorithms.

Glossary and Rules of the Game.

Anatomy of DFS in Digraphs.

Reachability and Transitive Closure.

Equivalence Relations and Partial Orders.

DAGs.

Topological Sorting.

Reachability in DAGs.

Strong Components in Digraphs.

Transitive Closure Revisited.

Perspective.

Representations.

Underlying Principles of MST Algorithms.

Prim's Algorithm and Priority-First Search.

Kruskal's Algorithm.

Boruvka's Algorithm.

Comparisons and Improvements.

Euclidean MST.

Underlying Principles.

Dijkstra's algorithm.

All-Pairs Shortest Paths.

Shortest Paths in Acyclic Networks.

Euclidean Networks.

Reduction.

Negative Weights.

Perspective.

Flow Networks.

Augmenting-Path Maxflow Algorithms.

Preflow-Push Maxflow Algorithms.

Maxflow Reductions.

Mincost Flows.

Network Simplex Algorithm.

Mincost-Flow Reductions.

Perspective.