Bytedance·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

Bytedance SRE screen, one coding question the whole time. Pretty standard grid traversal problem but they wanted you to actually talk through tradeoffs between BFS, DFS, and Union-Find which I was not expecting to go that deep on.

Questions Asked (1)

Given a binary grid where 1s represent land and 0s represent water, count the number of islands. An island is a group of 1-cells connected horizontally or vertically. Walk through your solution and discuss the complexity tradeoffs between different approaches.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went straight to DFS because it's the path of least resistance for this kind of problem.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints (e.g., grid size, memory limits) and then present a DFS/BFS solution that traverses each cell once, marking visited land. After explaining the basic approach, discuss tradeoffs between DFS, BFS, and Union-Find, focusing on time/space complexity and practical considerations like recursion depth and parallelism.

Pro tip: Mention that BFS avoids recursion depth issues and is safer for large grids, but Union-Find can be more efficient if the grid is dynamic or if you need to process multiple queries. This shows you think beyond the basic solution.

1. Clarify constraints and edge cases

Ask about grid dimensions, memory limits, and whether the grid can be modified. Discuss edge cases like empty grid, all water, or all land.

2. Present a baseline solution

Explain a DFS or BFS approach: iterate through each cell, and when encountering unvisited land, increment island count and traverse all connected land to mark visited.

3. Analyze complexity

State that time complexity is O(M*N) since each cell is visited once, and space complexity is O(M*N) in the worst case for the visited set or recursion stack.

4. Discuss alternative approaches and tradeoffs

Compare DFS (simple but recursion depth risk), BFS (iterative, uses queue), and Union-Find (good for dynamic connectivity, but higher constant factors). Mention in-place modification vs. extra space.

5. Optimize and conclude

Suggest optimizations like using a direction array, early termination, or parallel processing for large grids. Summarize the best approach based on constraints.

Key Points to Mention

Time complexity O(M*N) and space complexity O(M*N) for visited set or recursion stack.
DFS vs. BFS: recursion depth vs. queue memory, and iterative vs. recursive tradeoffs.
Union-Find approach: O(M*N α(M*N)) time, but useful for dynamic grids or multiple queries.
In-place modification of the grid to mark visited saves space but may not be allowed.
Handling large grids: BFS avoids stack overflow; consider iterative DFS with explicit stack.
Edge cases: empty grid, single row/column, all 1s or all 0s.

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