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Bytedance·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Bytedance software engineer interview with a grid pathfinding problem that looks deceptively simple until you realize brute force won't cut it. Three solid approaches exist and they probably wanted to see at least two of them.

Questions Asked (1)

Q1

Given an n×n grid of non-negative integer weights, find a path from the top-left to the bottom-right cell (moving in four directions) that minimizes the maximum cell value encountered along the path. Return that minimum possible maximum value.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I went straight for a modified Dijkstra where the priority queue key is the running max rather than the running sum.

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AI HintsAI Generated

Suggested Approach

This is a minimax path problem where we need to minimize the maximum cell value along a path. The optimal strategy is to binary search on the answer (the maximum allowed value) and check if a path exists using only cells with values ≤ that threshold via BFS/DFS. Alternatively, use a priority queue (Dijkstra-like) to always expand the cell with the smallest maximum value so far.

Pro tip: Mention that the binary search + BFS approach runs in O(n^2 log(maxVal)) time and O(n^2) space, which is efficient for large grids. Also note that the priority queue approach can be more direct and avoids the log factor, but both are acceptable; showing awareness of trade-offs impresses interviewers.

1. Clarify the problem and constraints

Confirm that movement is allowed in four directions (up, down, left, right) and that we want to minimize the maximum cell value along the path. Ask about grid size and value ranges to decide on the algorithm.

2. Choose an approach

Decide between binary search on the answer with BFS/DFS feasibility check, or a modified Dijkstra using a priority queue. Explain the trade-offs: binary search is simpler to reason about, while Dijkstra directly computes the answer.

3. Implement the feasibility check or Dijkstra

For binary search: define a function that checks if a path exists from start to end using only cells with value ≤ threshold. For Dijkstra: use a min-heap keyed by the maximum value encountered so far, and update neighbors accordingly.

4. Analyze complexity and edge cases

State the time and space complexity of your chosen approach. Discuss edge cases: n=1, all cells same value, start or end being the maximum, and unreachable paths (though grid is fully connected).

5. Test with examples

Walk through a small example (e.g., 3x3 grid) to verify the algorithm. If time permits, mention potential optimizations like early termination or using union-find for offline processing.

Key Points to Mention

  • Binary search on the answer with BFS/DFS feasibility check: O(n^2 log(maxVal)) time, O(n^2) space.
  • Dijkstra-like approach with priority queue: O(n^2 log n) time, O(n^2) space, directly computes the minimax value.
  • The problem is equivalent to finding the minimum threshold such that start and end are connected in the subgraph of cells with value ≤ threshold.
  • Four-directional movement means we must consider all neighbors, not just right and down.
  • Edge cases: n=1 (answer is the single cell), start or end being the maximum value, and all cells having the same value.
  • Trade-offs: binary search is simpler but may do redundant work; Dijkstra is more direct but requires a priority queue.

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