What are the advantages of using depth-first search?

What are the advantages of using depth-first search?

Depth-first search (DFS) has several advantages, including lower memory usage compared to breadth-first search, as it only needs to store a single path from the root to a leaf node, along with unexplored sibling nodes. This makes it more efficient for deep trees.

Are there specific scenarios where DFS is preferred?

Yes, DFS is particularly useful in scenarios like solving puzzles, pathfinding in mazes, and topological sorting in graphs. It's also effective when the solution is expected to be deep in the search space.

What are the limitations of depth-first search?

DFS can get stuck in deep paths and may not find the shortest path in unweighted graphs. It also risks running into infinite loops if cycles are present unless properly managed.

How does DFS compare to breadth-first search?

DFS is generally more memory efficient than breadth-first search, but BFS guarantees the shortest path in unweighted graphs, making it preferable in those cases.