Snapchat·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026

Summary

Snapchat SWE interview with a grid-based coding problem that's basically a twist on a classic LC problem. Not too bad if you've seen the original, but the follow-up about optimization kept things interesting.

Questions Asked (1)

Given a binary grid where 1s represent land and 0s represent water, find the maximum perimeter among all islands in the grid. An island is a group of 4-connected land cells, and perimeter counts edges that touch water or the grid boundary.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Recognized it as a variant of the island perimeter problem pretty fast, which helped.

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AI HintsAI Generated

Suggested Approach

Use BFS/DFS to traverse each island, computing its perimeter by counting water/boundary edges for each land cell. Track the maximum perimeter across all islands. Discuss trade-offs between DFS recursion depth and BFS queue memory.

Pro tip: Mention that you can compute perimeter during traversal without extra space by checking each cell's four neighbors, and highlight the importance of handling large grids with iterative BFS to avoid stack overflow.

1. Clarify and Confirm

Restate the problem to ensure understanding: 4-connected islands, perimeter definition, and edge cases like empty grid or no land. Ask about grid size constraints to discuss scalability.

2. Choose Traversal Strategy

Decide between DFS and BFS. DFS is simpler but may cause stack overflow for large islands; BFS uses a queue and is safer for deep recursion. Mention iterative DFS as an alternative.

3. Compute Perimeter Efficiently

During traversal, for each land cell, check its four neighbors. If a neighbor is water or out of bounds, increment perimeter. Avoid revisiting cells by marking them visited.

4. Track Maximum and Handle Edge Cases

Maintain a global max perimeter. After traversing each island, update max. Handle edge cases: all water (return 0), single cell (perimeter 4), and multiple islands.

5. Analyze Complexity and Optimize

Time complexity O(m*n) since each cell visited once. Space complexity O(m*n) for visited set or queue. Discuss potential optimizations like modifying grid in-place to mark visited.

Key Points to Mention

Use BFS/DFS to traverse each island and compute perimeter by checking 4 neighbors.
Mark visited cells to avoid infinite loops and double-counting.
Perimeter contribution: each land cell adds 4 minus number of adjacent land cells.
Time complexity O(m*n), space complexity O(m*n) for visited set or queue.
Trade-offs: DFS recursion depth vs BFS queue memory; iterative DFS as alternative.
Edge cases: empty grid, no land, single cell, multiple islands.

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