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Snapchat·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
Apr 2026Remote

Summary

Snapchat coding interview with a grid-based reachability problem that started simple and then got way more interesting once they added the dynamic blocker twist. The follow-up about incremental data structures is where things got real.

Questions Asked (1)

Q1

Given a grid with a start, an end, and some blocked cells, determine if the end is reachable from the start. Then: a new blocker gets added to the grid. How do you handle reachability efficiently going forward? Walk through the trade-offs between recomputing from scratch versus maintaining some incremental structure.

Algorithms & Data StructuresTechnical Trade-offsSystem Design
Author's notes

The BFS part I got through fine, pretty standard.

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AI HintsAI Generated

Suggested Approach

Start by explaining the baseline BFS/DFS solution for static reachability, then analyze the dynamic update scenario. Compare recomputing from scratch (O(V+E) per update) against incremental approaches like maintaining a reachability tree or using union-find with rollback, discussing trade-offs in time, space, and implementation complexity.

Pro tip: Emphasize that the choice depends on the frequency of updates and queries; for a single update, recomputation is often simpler and fast enough, but for many updates, incremental structures pay off. Mention that in practice, you'd also consider the grid size and whether blockers are permanent.

1. Clarify the problem and constraints

Ask about grid size, number of updates, whether blockers are permanent, and if queries are interleaved with updates. This determines the appropriate algorithm.

2. Present the baseline solution

Explain that for a static grid, BFS or DFS from start to end works in O(V+E) time. For a single update, you can simply re-run BFS/DFS.

3. Analyze the dynamic update scenario

Discuss that adding a blocker can only disconnect the graph if the blocker lies on all paths. Recomputing from scratch is O(V+E) per update, which may be acceptable for few updates but inefficient for many.

4. Propose incremental approaches

Describe maintaining a reachability tree (e.g., BFS tree) and checking if the new blocker is a bridge; if so, recompute only affected parts. Alternatively, use union-find with rollback or dynamic connectivity data structures, noting their complexity.

5. Compare trade-offs and conclude

Weigh recomputation (simple, O(V+E) per update) against incremental (complex, potentially faster updates). Recommend based on expected update frequency and grid size.

Key Points to Mention

  • BFS/DFS for static reachability and its time complexity O(V+E).
  • The impact of adding a blocker: only disconnects if it's a bridge or cut vertex on all paths.
  • Recomputation from scratch: simple but O(V+E) per update, may be fine for few updates.
  • Incremental approach: maintain a BFS tree and check if blocker is a bridge; if so, recompute only affected subtree.
  • Union-find with rollback or dynamic connectivity for handling updates efficiently, but with higher implementation complexity.
  • Trade-offs: time vs. space vs. implementation complexity; choose based on update frequency and grid size.

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