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Parallelize the lock BFS safely

Last updated: Mar 29, 2026

Quick Overview

Parallelize the lock BFS safely evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • hard
  • Snapchat
  • System Design
  • Software Engineer

Parallelize the lock BFS safely

Company: Snapchat

Role: Software Engineer

Category: System Design

Difficulty: hard

Interview Round: Technical Screen

Follow-up: If multiple threads are available, how would you parallelize the BFS for the rotating-lock problem? Describe how to partition work across threads, maintain BFS level ordering if required, implement a thread-safe visited set and queues, prevent duplicate exploration, and evaluate trade-offs such as contention, memory overhead, and determinism.

Quick Answer: Parallelize the lock BFS safely evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/System Design/Snapchat

Parallelize the lock BFS safely

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Jul 31, 2025, 12:00 AM
hardSoftware EngineerTechnical ScreenSystem Design
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Parallelize the lock BFS safely

Parallelizing BFS for the Rotating-Lock Problem

Context

You are given the classic rotating-lock problem (e.g., a 4-wheel lock from "0000" to a target like "0202" with deadends). In the single-threaded solution, we use BFS over the implicit state graph where each state has up to 8 neighbors (turn each wheel +1 or −1 mod 10). The goal is to find the minimum number of moves.

Assume:

  • State space size is at most 10,000 (for a 4-digit lock with digits 0–9).
  • There is a set of deadend states to avoid.

Task

If multiple threads are available, design a parallel BFS for this problem. Describe:

  1. How to partition work across threads.
  2. How to maintain BFS level ordering (if required for shortest-path correctness).
  3. How to implement a thread-safe visited set and queues.
  4. How to prevent duplicate exploration across threads.
  5. Trade-offs: contention, memory overhead, determinism, and when to prefer one approach over another.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask Guidance

  • Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
  • State explicit assumptions before making sizing or architecture decisions.
  • Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers Guidance

  • A scoped requirements summary with concrete non-goals and success metrics.
  • API, data model, architecture, consistency, capacity, and operations.
  • Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
  • A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions Guidance

  • What breaks first at 10x traffic or data volume?
  • How would you degrade gracefully during dependency failures?
  • What metrics and alerts would prove the design is healthy after launch?

Submit Your Answer to Earn 20XP

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