Undirected Graph

Algorithm Starting at some arbitrarily chosen vertex s (s stands for start vertex) , we mark v so that we know we’ve visited it, process v, and  then visit i.e. mark the vertex as visited and process all of v’s neighbors.  Now that we’ve visited and processed all of v’s neighbors,  we need to visit and process all of v’s neighbors neighbors Pseudocode BFS(graph G, vertex s) $all nodes initially unexplored$ \-mark s as explored let Q = queue data structure, initialized with s while (Q not empty) remove the first node of Q, call it v for each edge (v, w): if w is unexplored mark w as explored add w to Q (at the end) We visit each node only once and each edge at most twice (for edge(v, w), we might encounter it when we’re at node v and at node w). [Read More]

Graphs consist of 2 ingredients : Vertices (V) , also called nodes and can be pictured as dots Edges (E) , the line connecting the nodes. Types of Graphs Depending on the edges, there two types of graphs: Undirected Graphs - A graph that entail edges with ordered pair of vertices, however it does not have direction define. Example of such a graph is the ‘Family tree of the Greek gods’ **Directed Graphs (**aka Arcs) - Directed Graph: A graph that entail edges with ordered pair of vertices and has direction indicated with an arrow. [Read More]