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Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026Remote

Summary

Meta SWE coding round, got a task manager design problem that looked straightforward but had enough moving parts to trip you up if you weren't careful about data structure choices.

Questions Asked (1)

Q1

Design a task manager program that supports adding tasks with a unique ID, name, priority, and deadline; deleting tasks by ID; filtering by priority or deadline; and sorting by priority or deadline.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The add and delete parts were fine, pretty routine.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a data structure that balances time complexity for all operations. Discuss trade-offs between different approaches (e.g., hash map + heap vs. balanced BST) and justify your choice based on expected usage patterns.

Pro tip: Mention that you would use a unique ID generator (like UUID or auto-increment) and consider thread-safety if the task manager is concurrent. Also, discuss how to handle edge cases like duplicate IDs or invalid priorities.

1. Clarify Requirements

Ask about expected scale, concurrency, persistence, and whether operations need to be optimized for specific patterns (e.g., frequent filtering vs. frequent additions).

2. Choose Data Structures

Propose a primary data structure (e.g., hash map for O(1) add/delete by ID) and auxiliary structures for efficient filtering and sorting (e.g., heaps or balanced trees for priority/deadline).

3. Design Operations

Detail how each operation (add, delete, filter, sort) will be implemented, including time and space complexity for each.

4. Discuss Trade-offs

Compare alternative designs (e.g., using a single sorted list vs. multiple indexes) and explain why your chosen approach is optimal for the given constraints.

5. Handle Edge Cases and Extensions

Address edge cases (e.g., deleting non-existent ID, empty results) and suggest possible extensions (e.g., persistence, concurrency, pagination).

Key Points to Mention

  • Use a hash map for O(1) add and delete by ID.
  • Maintain separate indexes (e.g., heaps or balanced BSTs) for priority and deadline to enable efficient filtering and sorting.
  • Discuss time complexity: add O(log n) if using heap, delete O(log n) if lazy deletion, filter O(k) where k is result size, sort O(n log n) or O(n) if using pre-sorted structures.
  • Consider memory overhead of maintaining multiple indexes and trade-offs with update operations.
  • Mention thread-safety and concurrency control if the system is multi-threaded.
  • Propose using a unique ID generator (e.g., UUID, auto-increment) and handling collisions.

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