How do BFS and DFS work in graph traversal?

Can you explain how BFS and DFS work in graph traversal?

Sure! BFS (Breadth-First Search) explores all neighbors at the present depth prior to moving on to nodes at the next depth level. DFS (Depth-First Search), on the other hand, explores as far as possible along a branch before backtracking.

How can I visualize these algorithms?

You can visualize BFS and DFS using graphs. For BFS, you can use a queue to keep track of nodes to explore, while for DFS, a stack or recursion is used. There are many online tools and libraries that can help with this.

Are there any specific use cases for BFS and DFS?

Yes! BFS is often used in finding the shortest path in unweighted graphs, while DFS is useful for topological sorting and solving puzzles like mazes.

Can you show me a simple example of each?

Absolutely! For BFS, imagine a tree structure where you start at the root and explore each level before going deeper. For DFS, you would start at the root and go as deep as possible down one branch before backtracking.