Applications of BFS or Breadth First Search have wide range of real world applications and theoretical problems in the computer science domain. From finding shortest path in unweighted graph to finding connected components, BFS is a powerful graph traversal algorithm that explores node level by level.
If I’m talking about the time complexity for this algorithm is O(V+E) where V represents the number of vertices in a graph and E represents the number of edges. BFS is efficient algorithm to solve difficult problems.
In this blog we will explore about the top applications of BFS or Breadth First Search in 2025 along with the complexity of BFS algorithm.
What are the applications of BFS or Breadth First Search?
BFS (Breadth First Search) is a graph traversal algorithm in which instead of going deeply to traverse the node we are traversing for nodes level by level.
Applications are the real life examples to understand how this algorithm works. Let’s explore BFS or Breadth First Search algorithm by diagram.
BFS visits nodes level by level, from left to right. BFS algorithm uses queue data structure to solve the traversing for a tree or graph in a level order.
- Start with root: 18
- Enqueue its children: 12, 30
- Dequeue 12, enqueue its child: 5
- Dequeue 30 (no children)
- Dequeue 5, enqueue its child: 13
- Dequeue 13, enqueue its child: 10
- Dequeue 10 (no children)
Top 7 Applications of BFS (Breadth First Search)
This section covers the top 7 applications of BFS or Breadth First Search that includes the shortest path in unweighted graph, social network analysis, web crawlers, level order traversal in trees, cycle detection un unweighted graphs, network broadcasting and finding connected components.
Shortest Path in Unweighted Graph
One of the most common applications of BFS is finding the shortest path in an unweighted graph. Since BFS explores all nodes at the current depth before moving to the next level it guarantees the shortest path from the source to any other node in terms of the number of edges. This makes BFS highly efficient for pathfinding problems where edge weights are uniform or irrelevant.
Social Network Analysis
In social network analysis BFS helps us understand how people are connected to each other. It can find the shortest link between two people and also helps in finding groups or communities in a network. For example it can show how many steps it takes to reach a friend of a friend. This is one of the common applications of BFS in apps like Facebook LinkedIn or Instagram.
Web Crawlers
Web crawlers use BFS to visit pages on the internet. The crawler starts from one page and visits all nearby links first before going deeper. This helps in collecting and indexing web pages in a proper order. Search engines like Google use this method to scan websites. This makes BFS very useful in building search tools.
Level Order Traversal in Trees
BFS is also used in level order traversal of trees. It means visiting all the nodes of the tree level by level from top to bottom. This is helpful in printing the tree structure or solving tree based problems. It is one of the simple and clear applications of BFS in data structures and programming.
Cycle Detection in Unweighted Graph
Another helpful application of BFS is cycle detection in unweighted graphs. When we use BFS to visit nodes we can keep track of the parent of each node. If we find a node that was already visited and it is not the parent then a cycle exists. This is useful in checking whether a graph is safe to use or not especially in computer networks and scheduling tasks.
Network Broadcasting
BFS is useful in network broadcasting. It helps send a message or signal from one computer to all other computers in a network. BFS makes sure the message travels step by step and reaches all parts of the network quickly. This is very useful in real time systems and communication networks where fast message delivery is needed.
Finding Connected Components
One more important application of BFS is in finding connected components of a graph. BFS starts from a node and finds all other nodes that are connected to it. Then it moves to the next unvisited node and repeats. This helps in finding different groups in a network or a graph. It is used in image processing social networks and clustering problems.
Know More About Applications of BFS Algorithm
Why is BFS preferred for finding the shortest path in an unweighted graph?
BFS is preferred because it explores nodes level by level. As a result it always finds the shortest path in terms of the number of edges. Unlike DFS which can go deep and miss shorter paths.
How does BFS help in real-world applications like social networks?
BFS helps by mapping how users are connected. Many social media platforms uses friend suggestion feature which is again the application of breadth first search algorithm.
What is the time complexity of BFS algorithm?
The time complexity for the BFS or Breadth First Search algorithm is O(V+E). V here is the vertices of graph whereas E are the edges present in the graph.