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  2. Adjacency list - Wikipedia

    en.wikipedia.org/wiki/Adjacency_list

    Then, 8| E | > | V | 2 /8 when | E |/| V | 2 > 1/64, that is the adjacency list representation occupies more space than the adjacency matrix representation when d > 1/64. Thus a graph must be sparse enough to justify an adjacency list representation. Besides the space trade-off, the different data structures also facilitate different operations.

  3. 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.

  4. Kosaraju's algorithm - Wikipedia

    en.wikipedia.org/wiki/Kosaraju's_algorithm

    Provided the graph is described using an adjacency list, Kosaraju's algorithm performs two complete traversals of the graph and so runs in Θ(V+E) (linear) time, which is asymptotically optimal because there is a matching lower bound (any algorithm must examine all vertices and edges).

  5. Tarjan's strongly connected components algorithm - Wikipedia

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

    [1]: 157 A common variation is to instead use v.lowlink := min(v.lowlink, w.lowlink). [3] [4] This modified algorithm does not compute the lowlink numbers as Tarjan defined them, but the test v.lowlink = v.index still identifies root nodes of strongly connected components, and therefore the overall algorithm remains valid. [2]

  6. Implicit graph - Wikipedia

    en.wikipedia.org/wiki/Implicit_graph

    [8] [9] Intersection graphs An interval graph is the intersection graph of a set of line segments in the real line. It may be given an adjacency labeling scheme in which the points that are endpoints of line segments are numbered from 1 to 2n and each vertex of the graph is represented by the numbers of the two endpoints of its corresponding ...

  7. Breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Breadth-first_search

    Input: A graph G and a starting vertex root of G. Output: Goal state.The parent links trace the shortest path back to root [9]. 1 procedure BFS(G, root) is 2 let Q be a queue 3 label root as explored 4 Q.enqueue(root) 5 while Q is not empty do 6 v := Q.dequeue() 7 if v is the goal then 8 return v 9 for all edges from v to w in G.adjacentEdges(v) do 10 if w is not labeled as explored then 11 ...

  8. 10 Classic Southern Holiday Recipes To Make Right Now

    www.aol.com/10-classic-southern-holiday-recipes...

    2. Hoppin’ John. Southerners are usually eating Hoppin’ John (a simmery mix of black-eyed peas and rice) on New Year's Day. Like most “vegetable” recipes from around this area, it contains ...

  9. Parallel breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Parallel_breadth-first_search

    In the CSR, all adjacencies of a vertex is sorted and compactly stored in a contiguous chunk of memory, with adjacency of vertex i+1 next to the adjacency of i. In the example on the left, there are two arrays, C and R. Array C stores the adjacency lists of all nodes.