Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Apr 2026Remote

Summary

Meta coding interview with a maze/grid navigation problem. The kind of question that sounds straightforward until you're actually implementing it live and second-guessing every recursive call.

Questions Asked (1)

You have two API functions for a mouse on a grid you can't see directly. One tells you if the mouse can move in a given direction without hitting a wall, the other actually moves the mouse and tells you if it found the cheese. The grid layout and cheese position are unknown. Write an algorithm to navigate the mouse to the cheese and track the path or step count.

Algorithms & Data StructuresAPI & Integrations

Author's notes

My first instinct was DFS with backtracking and I think that was right, but implementing it cleanly with the visited set tripped me up.

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AI HintsAI Generated

Suggested Approach

Treat the grid as an unknown graph and use a systematic exploration algorithm like DFS or BFS with backtracking to guarantee finding the cheese. Maintain a visited set and a path stack to track the route and step count, leveraging the two APIs to sense and move.

Pro tip: Clarify the API semantics upfront: does the move function return success/failure, and can you detect when you've returned to a previous cell? This determines whether you need to track orientation and position explicitly.

1. Clarify API behavior and constraints

Ask about the move function's return value, whether the mouse can move diagonally, and if there's a limit on steps or memory. Confirm if the grid is finite and if the cheese is guaranteed reachable.

2. Model the problem as graph exploration

Represent each cell as a node and possible moves as edges. Use the canMove API to discover neighbors and the move API to traverse, treating the unknown grid as a graph to explore.

3. Choose an exploration algorithm

Select DFS with backtracking for simplicity and low memory, or BFS for shortest path if step count matters. Both guarantee finding the cheese if reachable.

4. Implement with state tracking

Maintain a visited set to avoid cycles, a path stack to record the route, and a step counter. After each move, check if cheese is found; if not, recursively explore unvisited directions.

5. Handle backtracking and termination

When no unvisited moves are available, backtrack by moving in the opposite direction of the last move. Terminate when cheese is found or all reachable cells are explored.

Key Points to Mention

Use DFS or BFS with backtracking to guarantee coverage of all reachable cells.
Maintain a visited set to avoid infinite loops and a path stack to reconstruct the route.
Track the step count by incrementing on each successful move.
Consider the trade-offs: DFS uses less memory but may not find shortest path; BFS finds shortest path but uses more memory.
Handle the case where the cheese is unreachable by returning failure after exhaustive search.
Optimize by using the canMove API to prune directions that hit walls before attempting to move.

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