BFS, which stands for Breadth-First Search, is a graph traversal algorithm used to explore all vertices of a graph in a breadthward motion. It starts at a specific vertex, known as the source, and visits all the adjacent vertices before moving on to the next level of vertices in a graph.
The algorithm works by systematically visiting each vertex of the graph in a breadthward motion, starting from the source vertex. It visits all the neighbors of the source vertex before moving on to the next level of vertices, which are the neighbors' neighbors. The algorithm proceeds level by level until it has visited all vertices reachable from the source vertex.
A key characteristic of BFS is that it visits all possible vertices at a given distance from the source vertex before moving on to the next level. This ensures that the algorithm explores the graph in a breadth-first manner, covering all vertices at the same level before proceeding to the next level.
BFS can be implemented using a queue data structure, where the source vertex is initially enqueued. The algorithm dequeues a vertex from the queue, visits it, and enqueues all its unvisited neighbors. This process continues until the queue becomes empty, indicating that all vertices have been visited.
BFS is commonly used in many applications such as finding the shortest path between two vertices, detecting cycles in a graph, and traversing trees and graphs in an organized manner. It provides an efficient way to explore and process graph structures systematically, making it a fundamental algorithm in graph theory and computer science.
