When do you use BFS versus DFS on a graph?
Reported in HubSpot USA engineering loops. Graph traversal question covering shortest paths, connectivity, and complexity.
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BFS explores level by level using a queue. It finds shortest paths in unweighted graphs and is ideal for minimum hops, broadcast, and nearest-neighbor problems. Time O(V + E), space O(V) for queue and visited set.
DFS dives deep along one path before backtracking, typically with recursion or an explicit stack. Use it for cycle detection, topological sort, connected components, path existence, and maze exploration where shortest path is not required.
On trees: BFS suits level-order traversal; DFS (pre/in/post-order) suits subtree aggregation and path sums. On large graphs, DFS recursion depth may overflow—prefer iterative DFS or BFS.
Always state representation (adjacency list vs matrix), visited tracking, and handling directed vs undirected edges. Mention bidirectional BFS for faster shortest path in large sparse graphs.
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