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Meta·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate
Apr 2026

Summary

Meta SWE interview with a multi-level coding assessment. This was level 2 of 4, building on top of a work-hours tracking system from the previous round by adding a ranking query on top of it.

Questions Asked (1)

Q1

Extend a work-hours tracking system to support a `top_n_workers(n, position)` method that returns the top N workers for a given position, ranked by total accumulated hours descending, with ties broken by worker ID lexicographically. Return results as formatted strings like `"<worker_id>(<total_time>)"`.

Algorithms & Data StructuresAPI & Integrations
Author's notes

The sorting part was fine, the annoying bit was remembering to handle the case where fewer than n workers exist for a position without crashing or returning garbage.

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AI HintsAI Generated

Suggested Approach

Clarify the data model and constraints first, then propose an efficient solution using a heap or sorting with a custom comparator. Discuss trade-offs between approaches and handle edge cases like ties and insufficient workers.

Pro tip: Mention that you would confirm whether the method should be called frequently and if the data changes often, as that determines whether to precompute or compute on the fly. Also, explicitly state how you handle ties and the output format.

1. Clarify requirements and constraints

Ask about the data structure for workers and hours, expected input size, frequency of calls, and whether the data is static or dynamic. Confirm the tie-breaking rule and output format.

2. Design the data aggregation

Explain how to compute total hours per worker for the given position, likely by iterating over records and summing hours, possibly using a hash map for efficiency.

3. Select the ranking algorithm

Choose between sorting all workers (O(m log m)) or using a min-heap of size N (O(m log N)) for top N. Discuss trade-offs based on N and m.

4. Implement tie-breaking and formatting

Define a comparator that sorts by total hours descending, then worker ID lexicographically ascending. Format each result as '<worker_id>(<total_time>)'.

5. Handle edge cases and test

Consider cases where N exceeds the number of workers, no workers for the position, or ties. Walk through an example to verify correctness.

Key Points to Mention

  • Time and space complexity of the chosen approach (e.g., O(m log N) with heap vs O(m log m) with sort).
  • Use of a custom comparator to enforce tie-breaking by worker ID lexicographically.
  • Efficiency considerations for large datasets, such as avoiding full sort when N is small.
  • Handling of edge cases: N > number of workers, empty position, negative or zero hours.
  • Potential for precomputation or caching if the method is called repeatedly with the same position.
  • Clear output formatting and adherence to the specified string format.

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