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  2. Reverse-delete algorithm - Wikipedia

    en.wikipedia.org/wiki/Reverse-delete_algorithm

    The reverse-delete algorithm is an algorithm in graph theory used to obtain a minimum spanning tree from a given connected, edge-weighted graph. It first appeared in Kruskal (1956) , but it should not be confused with Kruskal's algorithm which appears in the same paper.

  3. Graph removal lemma - Wikipedia

    en.wikipedia.org/wiki/Graph_removal_lemma

    In graph theory, the graph removal lemma states that when a graph contains few copies of a given subgraph, then all of the copies can be eliminated by removing a small number of edges. [1] The special case in which the subgraph is a triangle is known as the triangle removal lemma .

  4. Graph rewriting - Wikipedia

    en.wikipedia.org/wiki/Graph_rewriting

    Yet another approach to graph rewriting, known as determinate graph rewriting, came out of logic and database theory. [2] In this approach, graphs are treated as database instances, and rewriting operations as a mechanism for defining queries and views; therefore, all rewriting is required to yield unique results (up to isomorphism), and this is achieved by applying any rewriting rule ...

  5. Go (programming language) - Wikipedia

    en.wikipedia.org/wiki/Go_(programming_language)

    [c] Go adds literal syntaxes for initializing struct parameters by name and for initializing maps and slices. As an alternative to C's three-statement for loop, Go's range expressions allow concise iteration over arrays, slices, strings, maps, and channels. [57] fmt.Println("Hello World!") is a statement.

  6. Graph operations - Wikipedia

    en.wikipedia.org/wiki/Graph_operations

    graph intersection: G 1 ∩ G 2 = (V 1 ∩ V 2, E 1 ∩ E 2); [1] graph join: . Graph with all the edges that connect the vertices of the first graph with the vertices of the second graph. It is a commutative operation (for unlabelled graphs); [2] graph products based on the cartesian product of the vertex sets:

  7. Graph partition - Wikipedia

    en.wikipedia.org/wiki/Graph_partition

    Consider a graph G = (V, E), where V denotes the set of n vertices and E the set of edges. For a (k,v) balanced partition problem, the objective is to partition G into k components of at most size v · (n/k), while minimizing the capacity of the edges between separate components. [1]

  8. Cut (graph theory) - Wikipedia

    en.wikipedia.org/wiki/Cut_(graph_theory)

    A cut C = (S, T) is a partition of V of a graph G = (V, E) into two subsets S and T. The cut-set of a cut C = (S, T) is the set {(u, v) ∈ E | u ∈ S, v ∈ T} of edges that have one endpoint in S and the other endpoint in T. If s and t are specified vertices of the graph G, then an s – t cut is a cut in which s belongs to the set S and t ...

  9. Transitive reduction - Wikipedia

    en.wikipedia.org/wiki/Transitive_reduction

    The transitive reduction of a finite directed graph G is a graph with the fewest possible edges that has the same reachability relation as the original graph. That is, if there is a path from a vertex x to a vertex y in graph G, there must also be a path from x to y in the transitive reduction of G, and vice versa.