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  2. Adjacency list - Wikipedia

    en.wikipedia.org/wiki/Adjacency_list

    An adjacency list representation for a graph associates each vertex in the graph with the collection of its neighbouring vertices or edges. There are many variations of this basic idea, differing in the details of how they implement the association between vertices and collections, in how they implement the collections, in whether they include both vertices and edges or only vertices as first ...

  3. 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.

  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. Kosaraju's algorithm - Wikipedia

    en.wikipedia.org/wiki/Kosaraju's_algorithm

    The only additional data structure needed by the algorithm is an ordered list L of graph vertices, that will grow to contain each vertex once. If strong components are to be represented by appointing a separate root vertex for each component, and assigning to each vertex the root vertex of its component, then Kosaraju's algorithm can be stated ...

  6. 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 ...

  7. Dijkstra's algorithm - Wikipedia

    en.wikipedia.org/wiki/Dijkstra's_algorithm

    1 function Dijkstra(Graph, source): 2 3 for each vertex v in Graph.Vertices: 4 dist[v] ← INFINITY 5 prev[v] ← UNDEFINED 6 add v to Q 7 dist[source] ← 0 8 9 while Q is not empty: 10 u ← vertex in Q with minimum dist[u] 11 remove u from Q 12 13 for each neighbor v of u still in Q: 14 alt ← dist[u] + Graph.Edges(u, v) 15 if alt < dist[v ...

  8. How To Wash Lettuce The Right Way - AOL

    www.aol.com/wash-lettuce-way-183955051.html

    The Best Way To Wash Lettuce. The best way to wash lettuce is to use cool running water and gently scrub each leaf, says Edwards. “I prefer to fill a bowl with cold water and submerge lettuce ...

  9. Maze generation algorithm - Wikipedia

    en.wikipedia.org/wiki/Maze_generation_algorithm

    Start with a grid full of walls. Pick a cell, mark it as part of the maze. Add the walls of the cell to the wall list. While there are walls in the list: Pick a random wall from the list. If only one of the cells that the wall divides is visited, then: Make the wall a passage and mark the unvisited cell as part of the maze.

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