Data Structures Questions Medium
Graph traversal refers to the process of visiting all the vertices or nodes of a graph in a systematic manner. It involves exploring or traversing the graph to access or search for specific nodes or to perform certain operations on the graph.
There are two commonly used algorithms for graph traversal:
1. Depth-First Search (DFS): DFS starts at a given node and explores as far as possible along each branch before backtracking. It uses a stack to keep track of the nodes to be visited. The algorithm visits a node, marks it as visited, and then recursively explores all its adjacent unvisited nodes. DFS is often implemented using recursion or a stack data structure.
2. Breadth-First Search (BFS): BFS explores all the vertices of a graph in breadth-first order, i.e., it visits all the vertices at the same level before moving to the next level. It uses a queue to keep track of the nodes to be visited. The algorithm starts at a given node, marks it as visited, and enqueues its adjacent unvisited nodes. It then dequeues a node and repeats the process until all nodes have been visited.
Both DFS and BFS are used for different purposes. DFS is useful for finding connected components, detecting cycles, and solving problems like topological sorting and finding strongly connected components. BFS, on the other hand, is often used to find the shortest path between two nodes, solve puzzles with multiple solutions, and perform level-order traversal.
In summary, graph traversal is the process of systematically visiting all the nodes of a graph, and DFS and BFS are two commonly used algorithms for this purpose.