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  2. In-place algorithm - Wikipedia

    en.wikipedia.org/wiki/In-place_algorithm

    Identifying the in-place algorithms with L has some interesting implications; for example, it means that there is a (rather complex) in-place algorithm to determine whether a path exists between two nodes in an undirected graph, [3] a problem that requires O(n) extra space using typical algorithms such as depth-first search (a visited bit for ...

  3. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    The prev array contains pointers to previous-hop nodes on the shortest path from source to the given vertex (equivalently, it is the next-hop on the path from the given vertex to the source). The code u ← vertex in Q with min dist[u] , searches for the vertex u in the vertex set Q that has the least dist[ u ] value.

  4. Disjoint-set data structure - Wikipedia

    en.wikipedia.org/wiki/Disjoint-set_data_structure

    One family of algorithms, known as path compression, makes every node between the query node and the root point to the root. Path compression can be implemented using a simple recursion as follows: function Find(x) is if x.parent ≠ x then x.parent := Find(x.parent) return x.parent else return x end if end function

  5. Range minimum query - Wikipedia

    en.wikipedia.org/wiki/Range_minimum_query

    Range minimum query reduced to the lowest common ancestor problem.. Given an array A[1 … n] of n objects taken from a totally ordered set, such as integers, the range minimum query RMQ A (l,r) =arg min A[k] (with 1 ≤ l ≤ k ≤ r ≤ n) returns the position of the minimal element in the specified sub-array A[l …

  6. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    This array records the path to any square s. The predecessor of s is modeled as an offset relative to the index (in q[i, j] ) of the precomputed path cost of s . To reconstruct the complete path, we lookup the predecessor of s , then the predecessor of that square, then the predecessor of that square, and so on recursively, until we reach the ...

  7. Clique problem - Wikipedia

    en.wikipedia.org/wiki/Clique_problem

    The existence of a clique of a given size is a monotone graph property, meaning that, if a clique exists in a given graph, it will exist in any supergraph. Because this property is monotone, there must exist a monotone circuit, using only and gates and or gates , to solve the clique decision problem for a given fixed clique size.

  8. Hamiltonian path problem - Wikipedia

    en.wikipedia.org/wiki/Hamiltonian_path_problem

    A verifier algorithm for Hamiltonian path will take as input a graph G, starting vertex s, and ending vertex t. Additionally, verifiers require a potential solution known as a certificate, c. For the Hamiltonian Path problem, c would consist of a string of vertices where the first vertex is the start of the proposed path and the last is the end ...

  9. Flood fill - Wikipedia

    en.wikipedia.org/wiki/Flood_fill

    For case #2, a path leading out of the area exists. Paint the pixel the painter is standing upon and move in the direction of the open path. For case #3, the two boundary pixels define a path which, if we painted the current pixel, may block us from ever getting back to the other side of the path.