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  2. Breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Breadth-first_search

    If G is a tree, replacing the queue of this breadth-first search algorithm with a stack will yield a depth-first search algorithm. For general graphs, replacing the stack of the iterative depth-first search implementation with a queue would also produce a breadth-first search algorithm, although a somewhat nonstandard one. [10]

  3. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    By contrast, a breadth-first search will never reach the grandchildren, as it seeks to exhaust the children first. A more sophisticated analysis of running time can be given via infinite ordinal numbers ; for example, the breadth-first search of the depth 2 tree above will take ω ·2 steps: ω for the first level, and then another ω for the ...

  4. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.

  5. Lexicographic breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Lexicographic_breadth...

    The algorithm is called lexicographic breadth-first search because the order it produces is an ordering that could also have been produced by a breadth-first search, and because if the ordering is used to index the rows and columns of an adjacency matrix of a graph then the algorithm sorts the rows and columns into lexicographical order.

  6. Parallel breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Parallel_breadth-first_search

    The breadth-first-search algorithm is a way to explore the vertices of a graph layer by layer. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms. For instance, BFS is used by Dinic's algorithm to find maximum flow in a graph.

  7. Tarjan's strongly connected components algorithm - Wikipedia

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

    It also maintains a value v.lowlink that represents the smallest index of any node on the stack known to be reachable from v through v's DFS subtree, including v itself. Therefore v must be left on the stack if v.lowlink < v.index, whereas v must be removed as the root of a strongly connected component if v.lowlink == v.index.

  8. Today's Wordle Hint, Answer for #1300 on Thursday, January 9 ...

    www.aol.com/todays-wordle-hint-answer-1300...

    If you’re stuck on today’s Wordle answer, we’re here to help—but beware of spoilers for Wordle 1300 ahead. Let's start with a few hints.

  9. Biconnected component - Wikipedia

    en.wikipedia.org/wiki/Biconnected_component

    A simple alternative to the above algorithm uses chain decompositions, which are special ear decompositions depending on DFS-trees. [3] Chain decompositions can be computed in linear time by this traversing rule. Let C be a chain decomposition of G. Then G is 2-vertex-connected if and only if G has minimum degree 2 and C 1 is the only cycle in C.