![]() Q.enqueue( w ) //Stores w in Q to further visit its neighbour Removing that vertex from queue,whose neighbour will be visited now Q.enqueue( s ) //Inserting s in queue until all its neighbour vertices are marked. Pseudocode BFS (G, s) //Where G is the graph and s is the source node the node that was inserted first will be visited first, and so on. The queue follows the First In First Out (FIFO) queuing method, and therefore, the neigbors of the node will be visited in the order in which they were inserted in the node i.e. To make this process easy, use a queue to store the node and mark it as 'visited' until all its neighbours (vertices that are directly connected to it) are marked. ![]() This will allow you to visit the child nodes of 1 first (i.e. Store them in the order in which they are visited. In the earlier diagram, start traversing from 0 and visit its child nodes 1, 2, and 3. While visiting the nodes in the layer of a graph, store them in a manner such that you can traverse the corresponding child nodes in a similar order. To avoid processing of same node again, use a boolean array which marks the node after it is processed. Therefore, in BFS, you must traverse all the nodes in layer 1 before you move to the nodes in layer 2.Ī graph can contain cycles, which may bring you to the same node again while traversing the graph. The distance between the nodes in layer 1 is comparitively lesser than the distance between the nodes in layer 2. First move horizontally and visit all the nodes of the current layer.You must then move towards the next-level neighbour nodes.Īs the name BFS suggests, you are required to traverse the graph breadthwise as follows: BFS is the most commonly used approach.īFS is a traversing algorithm where you should start traversing from a selected node (source or starting node) and traverse the graph layerwise thus exploring the neighbour nodes (nodes which are directly connected to source node). The most common way of tracking vertices is to mark them. The order in which the vertices are visited are important and may depend upon the algorithm or question that you are solving.ĭuring a traversal, it is important that you track which vertices have been visited. While using certain graph algorithms, you must ensure that each vertex of the graph is visited exactly once. Graph traversal means visiting every vertex and edge exactly once in a well-defined order.
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