Roblox·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Did a technical phone screen for a Software Engineer role at Roblox. One coding question, grid traversal, pretty standard stuff but they pushed on implementation details more than I expected.

Questions Asked (1)

Given a 2D grid with walkable cells and obstacles, a start cell and an end cell, determine if a character can reach the end using 4-directional movement. Walk through your implementation and explain how you handle visited tracking.

Algorithms & Data Structures

Author's notes

I went with DFS because it felt faster to code under pressure.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (grid size, obstacles, start/end validity) and choose BFS for shortest path or DFS for simplicity. Walk through the algorithm step-by-step, emphasizing visited tracking to avoid cycles, and analyze time/space complexity. Optionally, discuss optimizations like in-place marking or bidirectional BFS.

Pro tip: Mention that you can mark visited cells in-place by modifying the grid (e.g., changing walkable to obstacle) to save space, but note the trade-off of mutating input. Also, consider edge cases like start == end or unreachable end early.

1. Clarify and Validate Input

Confirm grid dimensions, movement directions, and whether start/end are valid walkable cells. Handle edge cases like start equals end or out-of-bounds start/end.

2. Choose Traversal Algorithm

Select BFS for shortest path or DFS for simplicity. Explain the choice based on problem requirements (e.g., BFS guarantees shortest path if needed).

3. Implement Traversal with Visited Tracking

Use a queue (BFS) or stack (DFS) to explore neighbors. Track visited cells using a separate boolean matrix or by modifying the grid in-place to avoid revisiting.

4. Check Termination and Return Result

During traversal, check if the end cell is reached; if so, return true. If traversal completes without reaching end, return false.

5. Analyze Complexity and Optimizations

State time complexity O(R*C) and space complexity O(R*C) for visited matrix (or O(min(R,C)) for BFS queue). Mention possible optimizations like bidirectional BFS or in-place marking.

Key Points to Mention

Use BFS for shortest path or DFS for simplicity; explain trade-offs.
Visited tracking prevents infinite loops and redundant work; use a boolean matrix or modify grid in-place.
Time complexity O(R*C) and space complexity O(R*C) for visited matrix (or O(min(R,C)) for BFS queue).
Handle edge cases: start/end out of bounds, start == end, no path exists.
Consider bidirectional BFS for optimization if shortest path is needed.
In-place marking saves space but mutates input; discuss trade-offs.

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