Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Round 2 AI coding interview at Meta for a Software Engineer role. It was a maze problem, which apparently has come up enough times that there's no shortage of prep material out there for it.

Questions Asked (1)

Solve a maze traversal problem, finding a path through a grid from start to finish.

Algorithms & Data Structures

Author's notes

Pretty well-documented problem in the prep community so I wasn't totally blindsided.

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AI HintsAI Generated

Suggested Approach

Clarify the maze representation, movement rules, and whether any path suffices or the shortest path is required. Then choose BFS for shortest path or DFS for any path, and walk through the algorithm with complexity analysis and edge cases.

Pro tip: Meta interviewers value clean, bug-free code and strong communication. Before coding, restate the problem and confirm assumptions; after coding, test with a small example and discuss trade-offs like memory vs. time.

1. Clarify the problem

Ask about grid dimensions, obstacle representation, allowed moves (4-directional or 8-directional), and whether the path must be shortest. Confirm start and end points and if diagonal moves are permitted.

2. Choose the algorithm

If shortest path is needed, use BFS; otherwise DFS is simpler. Explain why BFS guarantees shortest path in unweighted grids and mention alternatives like A* if heuristics are allowed.

3. Outline the approach

Describe using a queue for BFS (or stack for DFS), a visited set to avoid cycles, and parent pointers to reconstruct the path. Mention boundary checks and obstacle handling.

4. Implement and test

Write clean code with helper functions if needed. Test with a small maze, including edge cases like no path, start equals end, and large grids.

5. Analyze complexity and optimize

State time and space complexity: O(R*C) for both BFS and DFS. Discuss potential optimizations like bidirectional BFS or using a visited matrix instead of a set for better performance.

Key Points to Mention

BFS guarantees shortest path in unweighted grids; DFS does not.
Use a visited set or matrix to avoid revisiting cells and infinite loops.
Reconstruct the path using parent pointers or by storing the path in the queue.
Time and space complexity are O(R*C) for both BFS and DFS.
Edge cases: no path, start equals end, empty grid, obstacles blocking all paths.
Trade-offs: BFS uses more memory but finds shortest path; DFS uses less memory but may find longer path.

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