Airbnb·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jul 2026

Summary

Airbnb SWE interview, technical phone screen, one coding question the whole time. Pretty standard BFS setup but they pushed on complexity and a follow-up variant that I hadn't fully thought through.

Questions Asked (1)

Given a grid maze with walls, a start position, and an exit, find the minimum number of moves to reach the exit. Return -1 if unreachable. Also discuss time/space complexity and how you'd adapt the solution if the start position were passed in separately instead of embedded in the grid.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went straight to BFS which was the right call, but I fumbled a bit explaining why BFS over DFS.

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AI HintsAI Generated

Suggested Approach

Model the maze as a graph and use BFS to find the shortest path, since each move has uniform cost. Clearly explain the algorithm, then analyze time and space complexity, and finally discuss how to adapt the solution if the start position is passed separately.

Pro tip: Mention that BFS is optimal for unweighted grids and that you can optimize space by using a visited set or modifying the grid in-place, but be mindful of side effects. Also, proactively discuss edge cases like unreachable exit or start at exit.

1. Clarify the problem

Confirm the grid representation (e.g., 0 for open, 1 for wall), movement allowed (4-directional), and that start/exit are distinct. Ask if diagonal moves are allowed or if there are any constraints.

2. Choose BFS and explain why

State that BFS guarantees the shortest path in an unweighted graph. Describe how you'll use a queue to explore level by level, marking visited cells to avoid cycles.

3. Walk through the algorithm

Outline the steps: enqueue start, track distance, dequeue and check for exit, enqueue valid neighbors, repeat until queue empty. Return distance when exit found, else -1.

4. Analyze complexity

Time: O(R*C) since each cell is visited at most once. Space: O(R*C) for the queue and visited set in the worst case.

5. Adapt for separate start parameter

If start is passed separately, modify the function signature to accept start coordinates. The algorithm remains the same, but you no longer need to search for the start in the grid, simplifying initialization.

Key Points to Mention

BFS is optimal for unweighted shortest path problems.
Use a queue for BFS and a visited set (or modify grid) to avoid revisiting cells.
Time complexity: O(R*C) where R and C are grid dimensions.
Space complexity: O(R*C) for queue and visited set.
Edge cases: start equals exit, unreachable exit, empty grid, start/exit on walls.
Adaptation: change function signature to accept start coordinates; no need to scan grid for start.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.