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  2. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    a depth-first search starting at the node A, assuming that the left edges in the shown graph are chosen before right edges, and assuming the search remembers previously visited nodes and will not repeat them (since this is a small graph), will visit the nodes in the following order: A, B, D, F, E, C, G.

  3. Tarjan's strongly connected components algorithm - Wikipedia

    en.wikipedia.org/wiki/Tarjan's_strongly_connected...

    The basic idea of the algorithm is this: a depth-first search (DFS) begins from an arbitrary start node (and subsequent depth-first searches are conducted on any nodes that have not yet been found). As usual with depth-first search, the search visits every node of the graph exactly once, refusing to revisit any node that has already been visited.

  4. Path-based strong component algorithm - Wikipedia

    en.wikipedia.org/wiki/Path-based_strong...

    It also uses a counter C of the number of vertices reached so far, which it uses to compute the preorder numbers of the vertices. When the depth-first search reaches a vertex v, the algorithm performs the following steps: Set the preorder number of v to C, and increment C. Push v onto S and also onto P. For each edge from v to a neighboring ...

  5. Iterative deepening depth-first search - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_depth...

    For the following graph: a depth-first search starting at A, assuming that the left edges in the shown graph are chosen before right edges, and assuming the search remembers previously-visited nodes and will not repeat them (since this is a small graph), will visit the nodes in the following order: A, B, D, F, E, C, G.

  6. Topological sorting - Wikipedia

    en.wikipedia.org/wiki/Topological_sorting

    An alternative algorithm for topological sorting is based on depth-first search.The algorithm loops through each node of the graph, in an arbitrary order, initiating a depth-first search that terminates when it hits any node that has already been visited since the beginning of the topological sort or the node has no outgoing edges (i.e., a leaf node):

  7. Control-flow graph - Wikipedia

    en.wikipedia.org/wiki/Control-flow_graph

    Some CFG examples: (a) an if-then-else (b) a while loop (c) a natural loop with two exits, e.g. while with an if...break in the middle; non-structured but reducible (d) an irreducible CFG: a loop with two entry points, e.g. goto into a while or for loop A control-flow graph used by the Rust compiler to perform codegen.

  8. Graph (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Graph_(abstract_data_type)

    In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within mathematics. A graph data structure consists of a finite (and possibly mutable) set of vertices (also called nodes or points ), together with a set of unordered pairs of these ...

  9. Graph traversal - Wikipedia

    en.wikipedia.org/wiki/Graph_traversal

    The problem of graph exploration can be seen as a variant of graph traversal. It is an online problem, meaning that the information about the graph is only revealed during the runtime of the algorithm. A common model is as follows: given a connected graph G = (V, E) with non-negative edge weights. The algorithm starts at some vertex, and knows ...