Snapchat·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Snapchat coding interview with a classic grid traversal problem. Pretty standard stuff if you've done any graph prep, but the follow-up questions about complexity and representation kept it from being a total freebie.

Questions Asked (1)

Given a grid with a start cell, an end cell, and some blocked cells, determine if there's a valid path from start to end moving in four directions without crossing blocked cells.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Went with BFS pretty quickly, which felt right.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (grid size, number of queries, memory limits) and then propose a graph traversal algorithm like BFS or DFS. Explain the trade-offs between BFS and DFS, and discuss optimizations such as bidirectional BFS or A* if applicable.

Pro tip: Demonstrate awareness of real-world constraints by mentioning that for large grids, BFS with a queue is often preferred over DFS due to stack overflow risks, and that bidirectional BFS can significantly reduce search space.

1. Clarify the problem

Ask about grid dimensions, whether multiple queries are expected, and if diagonal moves are allowed. Confirm that movement is only up, down, left, right and that blocked cells cannot be traversed.

2. Choose an algorithm

Select BFS for shortest path or DFS for any path. Discuss trade-offs: BFS uses more memory but finds shortest path; DFS uses less memory but may be slower and risk stack overflow.

3. Outline the approach

Describe how to represent the grid (e.g., 2D array or set of blocked cells) and how to track visited cells. Explain the traversal process step by step.

4. Analyze complexity

State time and space complexity: O(R*C) for both BFS and DFS, where R and C are grid dimensions. Mention that bidirectional BFS can reduce time to O(b^(d/2)) in some cases.

5. Discuss optimizations and edge cases

Mention bidirectional BFS, A* with Manhattan distance heuristic, and handling edge cases like start or end being blocked, or start equals end.

Key Points to Mention

BFS vs DFS trade-offs: BFS guarantees shortest path, DFS uses less memory but may not find shortest path.
Time and space complexity: O(R*C) for both, but bidirectional BFS can be faster.
Handling edge cases: start or end blocked, start equals end, no path exists.
Optimizations: bidirectional BFS, A* with Manhattan distance heuristic.
Data structures: queue for BFS, stack for DFS, visited set or 2D boolean array.
Real-world considerations: memory limits, recursion depth for DFS, and potential for parallelization.

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