Breadth First Search Algorithm
How it works
Imagine you’re on a social network, trying to figure out how you’re connected to others. You start with your own profile and identify your immediate friends, those you’re directly linked to (your immediate neighbours). You maintain a list of these friends to ensure you don’t miss anyone.
You then visit each of these friends’ profiles, explore their connections, and add them to your list (visiting all nodes and immediate neighbours). This process repeats for each friend, expanding your exploration gradually. By doing this systematically, you gradually explore the entire social network, moving from one user to another, marking them as visited (following your friend’s list), and uncovering all your connections and how they relate to one another.
This strategy is like Breadth First Search (BFS), which helps you uncover all the connections in your social network, ensuring you don’t miss any potential friends or connections.
Benefits
- Efficient: It searches through nodes in an organized way, finding optimal paths.
- Minimal memory usage: It manages nodes to explore with a queue, without needing to store the entire web of potential paths.
Real-life application
In social networks, BFS can be used to find how users are connected, identify mutual friends, and suggest new connections. It helps discover the shortest path between two users.
