Airbnb·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

May 2026

Summary

Airbnb software engineer interview with a simulation problem that looked deceptively straightforward on the surface. The water-pouring logic has enough edge cases to trip you up if you try to code before fully thinking through the flow.

Questions Asked (1)

Given an elevation map represented as an array of integer heights, simulate dropping V units of water at index K. Each water drop flows left as far as possible to a strictly lower position, then right if blocked, then stays at K if neither direction works. Return the resulting height array.

Algorithms & Data Structures

Author's notes

I started coding way too fast and got the left-scan logic backwards.

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AI HintsAI Generated

Suggested Approach

Clarify the water flow rules and edge cases, then design an efficient simulation. For each unit, find the nearest strictly lower position to the left; if none, find the nearest strictly lower position to the right; otherwise, keep it at K. Use a stack or precomputed arrays to avoid O(V*N) time.

Pro tip: Discuss trade-offs between simulation and precomputation, and mention that the problem can be solved in O(N) preprocessing and O(1) per drop using monotonic stacks or segment trees, which is crucial for large V.

1. Clarify the problem

Ask questions to confirm the flow rules: does water flow to the nearest strictly lower position? What if multiple lower positions exist? Confirm that water accumulates and changes heights, affecting subsequent drops.

2. Design the simulation

For each water unit, scan left from K to find the first index with height < current height at K. If found, increment that height and update K to that index? Actually, the problem says 'flows left as far as possible to a strictly lower position', so it moves to the leftmost strictly lower position? Clarify: typically it means the nearest strictly lower position to the left. Then if blocked, try right. If neither, stay at K.

3. Optimize with data structures

Precompute for each index the nearest strictly lower index to the left and right using monotonic stacks. Then each drop can be processed in O(1) by checking these precomputed indices, updating heights and possibly updating the precomputed arrays dynamically.

4. Handle dynamic updates

Since heights change after each drop, the precomputed nearest lower indices may become invalid. Consider using a balanced BST or segment tree to maintain the heights and query the nearest lower position efficiently.

5. Analyze complexity and test

Discuss time and space complexity. Test with edge cases: V=0, K at boundaries, all heights equal, strictly decreasing/increasing arrays.

Key Points to Mention

Clarify the exact flow rule: 'flows left as far as possible to a strictly lower position' likely means the nearest strictly lower position to the left, not the leftmost.
Water accumulates, so heights change after each drop, affecting subsequent flow.
Naive simulation is O(V*N) which may be too slow for large V; need efficient data structures.
Use monotonic stacks to precompute nearest lower elements, but updates require dynamic structures like segment trees or balanced BSTs.
Consider using a priority queue or union-find to skip over non-lower positions efficiently.
Edge cases: K at 0 or N-1, all heights equal, V large, heights can become equal after drops.

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