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

IntermediatePrefer not to say
Jun 2026

Summary

Airbnb coding round that went sideways fast. The question itself was reasonable but the interviewer showed up underprepared, with a broken JavaScript test class she hadn't vetted, and the whole session devolved into live debugging her own code rather than evaluating mine.

Questions Asked (1)

Q1

Implement a merged iterator over multiple streams (byte or char iterators) that reads one element from each stream in round-robin order, skipping exhausted streams. Must support has_next() and next().

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The question itself is fine, pretty standard iterator design.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases (e.g., empty streams, null inputs, thread safety). Then design a class that maintains a list of active iterators, a current index, and a method to advance to the next non-exhausted iterator. Implement has_next() and next() with careful handling of iterator removal and index wrapping.

Pro tip: Demonstrate awareness of real-world constraints: discuss how to handle concurrent modification, memory efficiency for large streams, and whether to pre-fetch elements for has_next() to avoid side effects. Mention that in production, you'd likely use a library like Guava's Iterators.concat or mergeSorted, but implementing it shows deeper understanding.

1. Clarify requirements and constraints

Ask about input types (byte/char iterators), whether streams can be added/removed dynamically, thread safety, and performance expectations. Confirm that has_next() should not consume elements.

2. Design the data structure

Propose maintaining a list of iterators, an index pointer, and possibly a cached next element. Explain how to skip exhausted iterators efficiently, e.g., by removing them from the list or advancing the index with modulo arithmetic.

3. Implement has_next() and next()

Describe the algorithm: has_next() scans from current index to find a non-exhausted iterator; next() returns the element from that iterator and advances the index. Handle the case where all iterators are exhausted.

4. Analyze complexity and trade-offs

Discuss time complexity: O(k) worst-case for has_next() where k is number of streams, but amortized O(1) if exhausted iterators are removed. Space complexity O(k). Compare with alternative approaches like pre-fetching or using a queue.

5. Test with edge cases

Walk through examples: empty list of streams, all streams empty, streams of different lengths, and interleaved exhaustion. Mention unit tests for these scenarios.

Key Points to Mention

  • Handling exhausted streams by removing them from the active list to avoid unnecessary checks.
  • Ensuring has_next() is idempotent and does not consume elements (unless caching is used).
  • Thread safety considerations: whether to synchronize methods or use concurrent data structures.
  • Memory efficiency: avoiding buffering entire streams; only holding references to iterators.
  • Edge cases: empty input, null iterators, and streams that throw exceptions during iteration.
  • Trade-offs between different implementations: e.g., using a queue of iterators vs. index-based round-robin.

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