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courses:cs211:winter2018:journals:nasona:chapter3 [2018/02/06 15:19] – [3.4 Bipartite Graphs: An Application of BFS] nasonacourses:cs211:winter2018:journals:nasona:chapter3 [2018/02/06 15:19] (current) – [3.2 Graph Connectivity and Traversal] nasona
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     * If there is no path between s and t, then there cannot be a node v that is in the connected component of each.     * If there is no path between s and t, then there cannot be a node v that is in the connected component of each.
   * A natural algorithm for producing all the connected components of a graph, by growing them one component at a time. We start with an arbitrary node s, and use BFS or DFS to generate its connected component.   * A natural algorithm for producing all the connected components of a graph, by growing them one component at a time. We start with an arbitrary node s, and use BFS or DFS to generate its connected component.
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 ==Additional Information== ==Additional Information==
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   * BFS and DFS spend work only on edges and nodes in the connected component containing the starting node. They never see any of the other, disjointed nodes or edges.   * BFS and DFS spend work only on edges and nodes in the connected component containing the starting node. They never see any of the other, disjointed nodes or edges.
   * The algorithm only spends a constant amount of work on a given edge or node in the iteration when the connected component it belongs to is under consideration. The total runtime is O(n + m).   * The algorithm only spends a constant amount of work on a given edge or node in the iteration when the connected component it belongs to is under consideration. The total runtime is O(n + m).
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 ==Additional Information== ==Additional Information==
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