Amazon·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026Remote

Summary

Amazon SWE coding round, one question the whole time: number of islands. Seemed straightforward but they kept pushing on scalability which is where things got interesting.

Questions Asked (1)

Given a 2D binary grid of '1's (land) and '0's (water), count the number of islands, where an island is a group of adjacent land cells connected horizontally or vertically.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I went with DFS pretty quickly, marking visited cells in place to avoid extra space.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (grid size, connectivity definition) and discuss trade-offs between BFS, DFS, and Union-Find. Then implement a solution using BFS or DFS with a visited set, explaining time and space complexity. Finally, test with edge cases and consider optimizations like in-place modification.

Pro tip: At Amazon, emphasize scalability and real-world applications (e.g., image processing, network connectivity). Mention how you'd handle massive grids with distributed BFS or Union-Find, showing system design thinking.

1. Clarify requirements and constraints

Ask about grid dimensions, connectivity (4-directional vs 8-directional), and whether input can be modified. Discuss potential edge cases like empty grid or all water.

2. Choose algorithm and justify

Compare BFS, DFS, and Union-Find in terms of time/space complexity, ease of implementation, and suitability for large-scale or streaming data. Select one and explain why.

3. Implement solution

Write clean code for the chosen algorithm. For BFS/DFS, iterate through each cell; when land is found, increment count and traverse all connected land, marking visited.

4. Analyze complexity and test

State time complexity O(m*n) and space complexity O(min(m,n)) for BFS or O(m*n) worst-case for DFS. Walk through test cases: single island, multiple islands, no islands, and large grid.

5. Discuss optimizations and trade-offs

Mention in-place modification to save space, using Union-Find for dynamic connectivity, or parallelizing BFS for distributed systems. Relate to Amazon's scale and performance needs.

Key Points to Mention

Time and space complexity analysis for each approach
Handling of edge cases (empty grid, all water, all land)
Trade-offs between BFS, DFS, and Union-Find
In-place modification to avoid extra space
Scalability considerations for large grids (e.g., distributed BFS)
Real-world applications like image processing or network connectivity

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