Graph Search / BFS / DFS Coding

Question

Waymo coding rounds consistently feature graph search problems (BFS and/or DFS). The specific problem is typically novel and not seen in standard LeetCode problem sets. In one reported instance, the problem was explained via a diagram rather than a text description, requiring extra time to understand before coding. Problems span graph traversal variants and may be combined with other algorithmic concepts (e.g., one round described as similar to a known LeetCode problem combined with a 'sliding window' style approach; another round described as a DFS problem similar to LeetCode 959). The candidate is expected to identify the correct traversal strategy, implement it correctly, and run it to completion within the interview time.

AceOffer · Accepted Answer

Waymo coding rounds consistently feature graph search problems (BFS and/or DFS). The specific problem is typically novel and not seen in standard LeetCode problem sets. In one reported instance, the problem was explained via a diagram rather than a text description, requiring extra time to understand before coding. Problems span graph traversal variants and may be combined with other algorithmic concepts (e.g., one round described as similar to a known LeetCode problem combined with a 'sliding window' style approach; another round described as a DFS problem similar to LeetCode 959). The candidate is expected to identify the correct traversal strategy, implement it correctly, and run it to completion within the interview time.

Reported follow-ups:
1. Can you walk me through the time and space complexity of your solution? (when: After initial solution is presented)
2. How would you handle cycles or disconnected components in this graph? (when: Candidate completes the basic traversal)

**Alternative approaches:** BFS for shortest-path variants (Guarantees shortest path in unweighted graphs; uses more memory (queue + visited set) than DFS but avoids stack overflow on large inputs.); DFS with recursion (Simple to implement for connectivity/reachability problems; risk of stack overflow on very deep graphs; may explore non-optimal paths first.)

Graph Search / BFS / DFS Coding

Problem Overview

Follow-up Arc

Approach Trade-offs

Practice

Approach	Notes
BFS for shortest-path variants	Guarantees shortest path in unweighted graphs; uses more memory (queue + visited set) than DFS but avoids stack overflow on large inputs.
DFS with recursion	Simple to implement for connectivity/reachability problems; risk of stack overflow on very deep graphs; may explore non-optimal paths first.