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Meta·Machine Learning Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Meta ML Engineer interview with a debugging-focused coding round. They handed me a broken maze solver and told me to find the bug. Pretty straightforward premise but the pressure of doing it live made me second-guess myself more than I should have.

Questions Asked (1)

Q1

You're given a BFS/DFS maze-solving implementation on a 2D grid that has a bug causing infinite loops or repeated cell processing. Find the bug and fix it so the search terminates correctly and returns a valid path.

Algorithms & Data StructuresRoot Cause Analysis
Author's notes

The fix itself isn't hard once you see it.

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AI HintsAI Generated

Suggested Approach

First, clarify the expected behavior of BFS/DFS on a grid and the symptoms of the bug (infinite loop or repeated processing). Then, systematically trace the algorithm to identify common pitfalls like missing visited checks or incorrect queue/stack management, and propose a fix with a test case.

Pro tip: Demonstrate a methodical debugging process by walking through a small example grid, showing exactly where the algorithm fails, and explaining how your fix prevents revisiting cells. This shows you can not only fix code but also validate it.

1. Understand the problem and expected behavior

Restate the goal: BFS/DFS should explore each reachable cell at most once and terminate, returning a path if found. Identify the symptoms: infinite loop or repeated processing indicates cells are being revisited.

2. Review the algorithm for common bugs

Check for missing or incorrect visited set, improper marking of visited cells (e.g., marking after dequeue instead of before enqueue), and incorrect neighbor iteration that might allow revisiting.

3. Trace through a small example

Simulate the algorithm on a tiny grid (e.g., 2x2) to observe where a cell gets processed multiple times. This pinpoints the exact line causing the issue.

4. Propose and implement the fix

Add or correct the visited check: mark cells as visited when they are added to the queue/stack, not when they are processed. Ensure the visited set is checked before adding neighbors.

5. Validate the fix and discuss edge cases

Test with the small example and consider edge cases like unreachable targets, empty grids, or obstacles. Confirm termination and correct path return.

Key Points to Mention

  • Importance of a visited set to avoid cycles and repeated processing
  • Marking visited at enqueue time (BFS) or push time (DFS) to prevent duplicates in the queue/stack
  • Correct neighbor generation: bounds checking and obstacle avoidance
  • Difference between BFS and DFS in terms of data structure (queue vs stack) and path reconstruction
  • Time and space complexity: O(V+E) with visited set, O(V) space
  • Testing with small grids and edge cases to ensure termination and correctness

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