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

IntermediatePrefer not to say
May 2026

Summary

Meta SWE coding round with an AI coding twist. The problem was finding three cards that sum to 15, broken into three parts: debug, implement, optimize. Spent too long on the bug hunt and had to lean on the AI to write the actual code for the later steps, but got through everything including follow-ups.

Questions Asked (1)

Q1

Given a set of cards, find three cards whose values sum to 15. The problem is broken into three parts: first identify a bug in provided code, then implement the algorithm from scratch, then optimize it.

Algorithms & Data StructuresRoot Cause AnalysisTechnical Trade-offs
Author's notes

The bug-finding part ate up way more time than I expected.

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AI HintsAI Generated

Suggested Approach

Start by carefully reviewing the provided code to identify the bug, explaining the root cause and its impact. Then, implement a correct algorithm from scratch, clearly stating assumptions and handling edge cases. Finally, discuss optimizations, comparing time and space complexity trade-offs and justifying your choices.

Pro tip: When debugging, articulate your thought process aloud and consider writing a test case that exposes the bug. For optimization, mention both algorithmic improvements (e.g., using hash sets) and micro-optimizations, but prioritize clarity and correctness first.

1. Understand the problem and constraints

Clarify the input format, card value ranges, and whether duplicates are allowed. Confirm the expected output (e.g., any three cards or all triplets).

2. Identify the bug in provided code

Trace through the code with sample inputs, looking for off-by-one errors, incorrect loop bounds, or mishandling of duplicates. Explain why the bug causes incorrect results.

3. Implement a correct algorithm from scratch

Choose a straightforward approach, such as sorting and using two pointers, or brute force for small inputs. Write clean, modular code and test with edge cases.

4. Optimize the algorithm

Analyze time and space complexity. Consider using a hash set to achieve O(n^2) time, or other optimizations like early termination. Discuss trade-offs.

5. Test and validate

Run through examples, including edge cases (e.g., no triplet, multiple triplets, negative values). Ensure the optimized solution matches the brute force results.

Key Points to Mention

  • Time and space complexity analysis for each approach (brute force O(n^3), two-pointer O(n^2), hash set O(n^2)).
  • Handling duplicates: whether to return unique triplets or any triplet, and how to avoid duplicate results.
  • Edge cases: empty input, fewer than three cards, no valid triplet, negative values, and large input sizes.
  • Root cause analysis: clearly explaining the bug, its impact, and how to fix it.
  • Trade-offs between simplicity and efficiency: when to use brute force vs. optimized solutions.
  • Code readability and maintainability: using meaningful variable names, modular functions, and comments.

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