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Algorithms in Java, Part 5: Graph Algorithms, Third Edition

Book Description

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. Michael Schidlowsky and Sedgewick have developed concise new Java implementations that both express the methods in a natural and direct manner and also can be used in real applications.

Algorithms in Java, 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. The natural match between Java classes and abstract data type (ADT) implementations makes the code more broadly useful and relevant for the modern object-oriented programming environment.

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

Coverage includes:

  • A complete overview of graph properties and types

  • Diagraphs and DAGs

  • Minimum spanning trees

  • Shortest paths

  • Network flows

  • Diagrams, sample Java code, and detailed algorithm descriptions

  • A landmark revision, Algorithms in Java, 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.

    Table of Contents

    1. Copyright
      1. Dedication
    2. Preface
      1. Algorithms
      2. Scope
      3. Use in the Curriculum
      4. Algorithms of Practical Use
      5. Programming Language
      6. Acknowledgments
    3. Java Consultant’s Preface
    4. Notes on Exercises
    5. V. Graph Algorithms
      1. 17. Graph Properties and Types
        1. 17.1. Glossary
          1. Exercises
        2. 17.2. Graph ADT
          1. Exercises
        3. 17.3. Adjacency-Matrix Representation
          1. Exercises
        4. 17.4. Adjacency-Lists Representation
          1. Exercises
        5. 17.5. Variations, Extensions, and Costs
          1. Exercises
        6. 17.6. Graph Generators
          1. Exercises
        7. 17.7. Simple, Euler, and Hamilton Paths
          1. Exercises
        8. 17.8. Graph-Processing Problems
          1. Exercises
      2. 18. Graph Search
        1. 18.1. Exploring a Maze
          1. Exercises
        2. 18.2. Depth-First Search
          1. Exercises
        3. 18.3. Graph-Search ADT Methods
          1. Exercises
        4. 18.4. Properties of DFS Forests
          1. Exercises
        5. 18.5. DFS Algorithms
          1. Exercises
        6. 18.6. Separability and Biconnectivity
          1. Exercises
        7. 18.7. Breadth-First Search
          1. Exercises
        8. 18.8. Generalized Graph Search
          1. Exercises
        9. 18.9. Analysis of Graph Algorithms
          1. Exercises
      3. 19. Digraphs and DAGs
        1. Exercises
        2. 19.1. Glossary and Rules of the Game
          1. Exercises
        3. 19.2. Anatomy of DFS in Digraphs
          1. Exercises
        4. 19.3. Reachability and Transitive Closure
          1. Exercises
        5. 19.4. Equivalence Relations and Partial Orders
          1. Exercises
        6. 19.5. DAGs
          1. Exercises
        7. 19.6. Topological Sorting
          1. Exercises
        8. 19.7. Reachability in DAGs
          1. Exercises
        9. 19.8. Strong Components in Digraphs
          1. Exercises
        10. 19.9. Transitive Closure Revisited
          1. Exercises
        11. 19.10. Perspective
          1. Exercises
      4. 20. Minimum Spanning Trees
        1. Exercises
        2. 20.1. Representations
          1. Exercises
        3. 20.2. Underlying Principles of MST Algorithms
          1. Exercises
        4. 20.3. Prim’s Algorithm and Priority-First Search
          1. Exercises
        5. 20.4. Kruskal’s Algorithm
          1. Exercises
        6. 20.5. Boruvka’s Algorithm
          1. Exercises
        7. 20.6. Comparisons and Improvements
          1. Exercises
        8. 20.7. Euclidean MST
          1. Exercises
      5. 21. Shortest Paths
        1. Exercises
        2. 21.1. Underlying Principles
          1. Exercises
        3. 21.2. Dijkstra’s Algorithm
          1. Exercises
        4. 21.3. All-Pairs Shortest Paths
          1. Exercises
        5. 21.4. Shortest Paths in Acyclic Networks
          1. Exercises
        6. 21.5. Euclidean Networks
          1. Exercises
        7. 21.6. Reduction
          1. Exercises
        8. 21.7. Negative Weights
          1. Exercises
        9. 21.8. Perspective
      6. 22. Network Flow
        1. 22.1. Flow Networks
          1. Exercises
        2. 22.2. Augmenting-Path Maxflow Algorithms
          1. Exercises
        3. 22.3. Preflow-Push Maxflow Algorithms
          1. Exercises
        4. 22.4. Maxflow Reductions
          1. Exercises
        5. 22.5. Mincost Flows
          1. Exercises
        6. 22.6. Network Simplex Algorithm
          1. Exercises
        7. 22.7. Mincost-Flow Reductions
          1. Exercises
        8. 22.8. Perspective
    6. References for Part Five