BFS vs DFS: Which is more efficient?

What are the main differences between BFS and DFS?

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

In terms of performance, which one is better?

It depends on the use case. BFS is generally better for finding the shortest path in unweighted graphs, while DFS can be more memory efficient and is better for searching deep structures.

Can you give an example where DFS outperforms BFS?

Sure! In scenarios like solving puzzles or navigating mazes where the solution is deep but not wide, DFS can find a solution faster and use less memory.

What are the time and space complexities of both algorithms?

BFS has a time complexity of O(V + E) and a space complexity of O(V), while DFS also has a time complexity of O(V + E) but can have a space complexity of O(h), where h is the maximum depth of the tree.