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Snapchat·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
Jul 2026Remote

Summary

Snapchat SWE interview with a deep parallel systems follow-up that honestly caught me off guard. The core problem was already tricky but then they pushed into multi-threaded territory and I had to think on my feet about trade-offs I hadn't fully prepared for.

Questions Asked (1)

Q1

If you have multiple threads available, how would you parallelize a BFS solution for the rotating-lock problem? Walk through how you'd split work across threads, keep level ordering intact, build a thread-safe visited set and queues, avoid re-exploring the same state, and weigh the trade-offs around contention, memory, and whether the result stays deterministic.

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

This one went sideways pretty fast.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and constraints, then outline a level-synchronous BFS where each thread processes a disjoint subset of the current frontier. Explain how to use thread-safe data structures and synchronization to maintain level ordering and avoid duplicate work, and discuss trade-offs like contention, memory overhead, and determinism.

Pro tip: Emphasize that the visited set must be updated atomically during neighbor expansion to prevent duplicate enqueues, and consider using a concurrent hash set with fine-grained locking or lock-free operations to minimize contention.

1. Clarify problem and constraints

Restate the rotating-lock problem (e.g., shortest sequence of rotations to reach target) and confirm assumptions like state space size, thread count, and whether determinism is required.

2. Design level-synchronous BFS

Explain that BFS processes level by level; parallelize by splitting the current frontier among threads, with a barrier after each level to maintain ordering.

3. Implement thread-safe structures

Use a concurrent queue for the next frontier and a thread-safe visited set (e.g., ConcurrentHashMap or lock-free set) with atomic check-and-set to avoid duplicate exploration.

4. Address synchronization and contention

Discuss partitioning work to reduce contention, using per-thread local queues merged at barriers, and minimizing lock granularity.

5. Analyze trade-offs

Weigh contention vs. parallelism, memory overhead of visited set and queues, and determinism (order of exploration may vary but shortest path length remains correct).

Key Points to Mention

  • Level-synchronous BFS with barriers to maintain level ordering
  • Thread-safe visited set using atomic operations or concurrent data structures
  • Partitioning the frontier across threads to balance load and reduce contention
  • Avoiding duplicate work via atomic check-and-set on visited states
  • Trade-offs: contention overhead, memory usage, and potential non-determinism in exploration order
  • Correctness: BFS still finds shortest path even if exploration order varies

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