Airbnb·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

Apr 2026

Summary

Airbnb coding interview with a simulation problem that builds on a prior terrain-generation question. Pretty niche problem set, felt like they expected you to have context from a previous round.

Questions Asked (1)

Given a terrain heights array, a pour column, and a volume, simulate pouring that many units of water at the specified column. Each unit flows to the lowest adjacent position (left preferred over right), accumulating like real water. Output the final grid showing terrain, water, and empty air.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

This is basically LC 755 but they want you to build it from scratch in context of a prior terrain problem.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases first, then propose a simulation approach that models water flow using a priority queue or BFS to find the lowest adjacent position. Discuss trade-offs between time/space complexity and accuracy, and consider optimizations like precomputing flow directions or using union-find for efficient water accumulation.

Pro tip: Demonstrate awareness of real-world water behavior by mentioning that water can pool and overflow, and that the 'left preferred over right' rule introduces a deterministic tie-breaking that must be handled consistently. Also, discuss how to handle large volumes efficiently, perhaps by batching units or using a mathematical approach to avoid unit-by-unit simulation.

1. Clarify Requirements and Constraints

Ask about input size, volume magnitude, and whether water can flow off the grid. Confirm the tie-breaking rule and output format.

2. Choose a Simulation Strategy

Decide between unit-by-unit simulation (simple but slow) and a more efficient approach like event-based simulation or using a priority queue to track water levels.

3. Design the Algorithm

Outline steps: start at pour column, for each unit find the lowest adjacent cell (left first), move water there, repeat until volume exhausted or water cannot move. Handle pooling and overflow.

4. Analyze Complexity and Optimize

Discuss time and space complexity. Propose optimizations like memoizing flow paths, using union-find for connected components, or simulating in batches.

5. Test with Edge Cases

Walk through examples: flat terrain, steep slopes, pour at edge, large volume, and tie-breaking scenarios to ensure correctness.

Key Points to Mention

Handling of water flow when multiple adjacent cells have the same lowest height, with left preference.
Water accumulation and pooling: water can fill a cell and then flow to adjacent cells, potentially creating a water level.
Overflow: if water reaches the edge of the grid, it may flow off (if allowed) or accumulate indefinitely.
Efficiency considerations: unit-by-unit simulation is O(volume * grid_size) which may be too slow; consider optimizations.
Data structures: priority queue (min-heap) to efficiently find lowest adjacent cell, or BFS/DFS for flow paths.
Trade-offs between exact simulation and approximation, and how to handle large volumes with mathematical modeling.

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