# What Is Breadth First Search in Data Structure?

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Scott Campbell

What Is Breadth First Search in Data Structure?

Breadth First Search (BFS) is a graph traversal algorithm that explores all the vertices of a graph in breadthward motion, i.e., exploring all vertices at the same depth before moving on to the next level. It is often used to solve problems like finding the shortest path, determining connected components, and detecting cycles in a graph.

## How Does Breadth First Search Work?

The BFS algorithm starts at a given source vertex and explores its adjacent vertices first before moving on to the next level of vertices. It uses a queue data structure to keep track of the vertices that need to be visited.

• Step 1: Enqueue the source vertex into the queue.
• Step 2: Mark the source vertex as visited.
• Step 3: While the queue is not empty, repeat steps 4 and 5.
• Step 4: Dequeue a vertex from the queue.
• Step 5: Visit and enqueue all unvisited adjacent vertices of the dequeued vertex. Mark them as visited.

The algorithm continues until all reachable vertices are visited or until there are no more vertices left in the queue. By visiting each vertex only once and exploring its neighbors before moving deeper into the graph, BFS ensures that it covers all nodes at each level before going deeper into subsequent levels.

## Applications of Breadth First Search

BFS has various applications in computer science and real-world scenarios. Some common use cases include:

• Shortest Path: BFS can be used to find the shortest path between two vertices in an unweighted graph.
• Connected Components: BFS can determine the connected components of a graph, i., groups of vertices that are reachable from each other.
• Cycle Detection: BFS can help detect cycles in a graph by checking if any visited vertex has an adjacent vertex that is already visited.
• Social Networking: BFS can be employed to find friends or connections in a social network by exploring connections up to a certain level of depth.
• Web Crawling: BFS is used in web crawling algorithms to systematically explore and discover web pages.

• BFS guarantees finding the shortest path between two vertices in an unweighted graph.
• It explores all vertices at each level, making it useful for applications involving levels or layers.
• The algorithm is relatively simple to understand and implement compared to some other graph traversal algorithms.

• BFS requires additional memory space to store the visited vertices and the queue, which may be a concern for large graphs with many vertices.
• In graphs with dense connectivity, BFS may visit many unnecessary vertices before reaching the desired destination.

In conclusion, Breadth First Search (BFS) is a fundamental graph traversal algorithm used to explore all vertices at each level before moving deeper into subsequent levels. It has various applications in solving problems related to shortest paths, connected components, cycle detection, and network exploration. While it has advantages in terms of simplicity and finding the shortest path, it also has limitations in terms of memory usage and inefficiency in densely connected graphs.