Table of Contents: the Boost Graph Library

1. Introduction to the BGL
2. Parallel BGL (distributed-memory parallel graph data structures and algorithms)
3. History
4. List of BGL Users
5. Publications
6. Acknowledgements
7. A Quick Tour of the Boost Graph Library.
8. Review of Elementary Graph Theory
9. Boost Graph Library Tutorial
   1. Property Maps
   2. The adjacency_list class
10. Examples
    1. File Dependency Example
    2. Six Degrees of Kevin Bacon
    3. Graph Coloring
    4. Sparse Matrix Ordering
11. Extending the Boost Graph Library
    1. Constructing graph algorithms with BGL
    2. Converting Existing Graphs to BGL
12. The Boost Graph Interface
    1. Graph
    2. Incidence Graph
    3. Bidirectional Graph
    4. Adjacency Graph
    5. Vertex List Graph
    6. Edge List Graph
    7. Vertex and Edge List Graph
    8. Adjacency Matrix
    9. Mutable Graph
    10. Property Graph
    11. Mutable Property Graph
13. The Property Map Library (technically not part of the graph library, but used a lot here)
14. Python bindings
15. Visitor Concepts
    1. BFS Visitor
    2. DFS Visitor
    3. Dijkstra Visitor
    4. Bellman Ford Visitor
    5. A* Visitor
    6. Event Visitor
    7. Planar Face Visitor
    8. TSP Tour Visitor
16. EventVisitorList Adaptors
    1. Event Visitor List
    2. bfs_visitor
    3. dfs_visitor
    4. dijkstra_visitor
    5. bellman_visitor
    6. astar_visitor
17. Event Visitors
    1. predecessor_recorder
    2. distance_recorder
    3. time_stamper
    4. property_writer
    5. property_put
    6. tsp_tour_visitor
    7. tsp_tour_len_visitor
18. Graph classes
    1. adjacency_list
    2. adjacency_matrix
    3. compressed_sparse_row_graph
19. Graph Adaptors
    1. subgraph
    2. edge_list
    3. reverse_graph
    4. filtered_graph
    5. Vector as Graph *
    6. Matrix as Graph*
    7. Leda Graph *
    8. Stanford GraphBase
    9. Implicit Graphs
       1. Multi-dimensional grid graph
20. Iterator Adaptors
    1. adjacency_iterator
    2. inv_adjacency_iterator
21. Traits classes
    1. graph_traits
    2. adjacency_list_traits
    3. property_map
22. Algorithms
    1. Named parameters (used in many graph algorithms)
    2. Basic Operations
       1. copy_graph
       2. transpose_graph
    3. Core Searches
       1. breadth_first_search
       2. breadth_first_visit
       3. depth_first_search
       4. depth_first_visit
       5. undirected_dfs
    4. Other Core Algorithms
       1. topological_sort
       2. transitive_closure
       3. lengauer_tarjan_dominator_tree
    5. Shortest Paths / Cost Minimization Algorithms
       1. dijkstra_shortest_paths
       2. dijkstra_shortest_paths_no_color_map
       3. bellman_ford_shortest_paths
       4. dag_shortest_paths
       5. johnson_all_pairs_shortest_paths
       6. floyd_warshall_all_pairs_shortest_paths
       7. r_c_shortest_paths - resource-constrained shortest paths
       8. astar_search
    6. Minimum Spanning Tree Algorithms
       1. kruskal_minimum_spanning_tree
       2. prim_minimum_spanning_tree
    7. Random Spanning Tree Algorithm
       1. random_spanning_tree
    8. Connected Components Algorithms
       1. connected_components
       2. strong_components
       3. biconnected_components
       4. articulation_points
       5. Incremental Connected Components
          1. initialize_incremental_components
          2. incremental_components
          3. same_component
          4. component_index
    9. Maximum Flow and Matching Algorithms
       1. edmonds_karp_max_flow
       2. push_relabel_max_flow
       3. boykov_kolmogorov_max_flow
       4. edmonds_maximum_cardinality_matching
    10. Minimum Cut Algorithms
        1. stoer_wagner_min_cut
    11. Sparse Matrix Ordering Algorithms
        1. cuthill_mckee_ordering
        2. king_ordering
        3. minimum_degree_ordering
        4. sloan_ordering
        5. sloan_start_end_vertices
    12. Graph Metrics
        1. ith_wavefront, max_wavefront, aver_wavefront, and rms_wavefront
        2. bandwidth
        3. ith_bandwidth
        4. brandes_betweenness_centrality
        5. minimum_cycle_ratio and maximum_cycle_ratio
    13. Graph Structure Comparisons
        1. isomorphism
        2. mcgregor_common_subgraphs
    14. Layout Algorithms
        1. Topologies used as spaces for graph drawing
        2. random_graph_layout
        3. circle_layout
        4. kamada_kawai_spring_layout
        5. fruchterman_reingold_force_directed_layout
        6. gursoy_atun_layout
    15. Clustering algorithms
        1. betweenness_centrality_clustering
    16. Planar Graph Algorithms
        1. boyer_myrvold_planarity_test
        2. planar_face_traversal
        3. planar_canonical_ordering
        4. chrobak_payne_straight_line_drawing
        5. is_straight_line_drawing
        6. is_kuratowski_subgraph
        7. make_connected
        8. make_biconnected_planar
        9. make_maximal_planar
    17. Miscellaneous Algorithms
        1. metric_tsp_approx
        2. sequential_vertex_coloring
        3. is_bipartite (including two-coloring of bipartite graphs)
        4. find_odd_cycle
23. Graph Input/Output
    1. AT&T Graphviz: read_graphviz, write_graphviz
    2. DIMACS Max-flow: read_dimacs_max_flow and read_dimacs_min_cut, write_dimacs_max_flow
    3. GraphML: read_graphml and write_graphml
24. Auxiliary Concepts, Classes, and Functions
    1. property
    2. ColorValue
    3. Buffer
    4. BasicMatrix
    5. incident
    6. opposite
    7. Tools for random graphs
       1. random_vertex
       2. random_edge
       3. generate_random_graph
       4. randomize_property
       5. erdos_renyi_iterator
       6. sorted_erdos_renyi_iterator
       7. plod_iterator
       8. small_world_iterator
25. Challenge and To-Do List
26. Trouble Shooting
27. Known Problems
28. FAQ
29. BGL Book Errata

* Items marked have not yet been documented.

Copyright © 2000-2001

Jeremy Siek, Indiana University ([email protected]) Lie-Quan Lee, Indiana University ([email protected]) Andrew Lumsdaine, Indiana University ([email protected])