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  2. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    It is also possible to use depth-first search to linearly order the vertices of a graph or tree. There are four possible ways of doing this: A preordering is a list of the vertices in the order that they were first visited by the depth-first search algorithm. This is a compact and natural way of describing the progress of the search, as was ...

  3. Iterative deepening depth-first search - Wikipedia

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

    Iterative deepening depth-first search; Class: Search algorithm: Data structure: Tree, Graph: Worst-case performance (), where is the branching factor and is the depth of the shallowest solution: Worst-case space complexity [1] Optimal: yes (for unweighted graphs)

  4. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    In depth-first search (DFS), the search tree is deepened as much as possible before going to the next sibling. To traverse binary trees with depth-first search, perform the following operations at each node: [3] [4] If the current node is empty then return. Execute the following three operations in a certain order: [5] N: Visit the current node.

  5. External memory graph traversal - Wikipedia

    en.wikipedia.org/wiki/External_memory_graph...

    Graph traversal is a subroutine in most graph algorithms. The goal of a graph traversal algorithm is to visit (and / or process) every node of a graph. Graph traversal algorithms, like breadth-first search and depth-first search, are analyzed using the von Neumann model, which assumes uniform memory access cost. This view neglects the fact ...

  6. 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.

  7. Iterator pattern - Wikipedia

    en.wikipedia.org/wiki/Iterator_pattern

    In C++, a class can overload all of the pointer operations, so an iterator can be implemented that acts more or less like a pointer, complete with dereference, increment, and decrement. This has the advantage that C++ algorithms such as std::sort can immediately be applied to plain old memory buffers, and that there is no new syntax to learn.

  8. Maze generation algorithm - Wikipedia

    en.wikipedia.org/wiki/Maze_generation_algorithm

    Randomized depth-first search on a hexagonal grid. The depth-first search algorithm of maze generation is frequently implemented using backtracking. This can be described with a following recursive routine: Given a current cell as a parameter; Mark the current cell as visited; While the current cell has any unvisited neighbour cells

  9. Trémaux tree - Wikipedia

    en.wikipedia.org/wiki/Trémaux_tree

    All depth-first search trees and all Hamiltonian paths are Trémaux trees. In finite graphs, every Trémaux tree is a depth-first search tree, but although depth-first search itself is inherently sequential, Trémaux trees can be constructed by a randomized parallel algorithm in the complexity class RNC.