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Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026Remote

Summary

Meta SWE coding round, one algorithmic problem the whole session. Sliding window stuff, but the exact-N-distinct constraint tripped me up more than I expected.

Questions Asked (1)

Q1

Given a string and an integer n, find the shortest contiguous substring that contains exactly n distinct characters. Discuss your algorithm's time and space complexity, handle edge cases, then implement it.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

My first instinct was sliding window but I kept conflating 'at most n distinct' with 'exactly n distinct' and that cost me probably five minutes of confused code.

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AI HintsAI Generated

Suggested Approach

Clarify the problem, including edge cases and constraints, then propose a sliding window approach with a hash map to track character frequencies. Explain how to maintain exactly n distinct characters by expanding and shrinking the window, and analyze time and space complexity before coding.

Pro tip: During implementation, use a while loop to shrink the window when distinct count exceeds n, and update the minimum length only when distinct count equals n. This avoids unnecessary checks and keeps the code clean.

1. Clarify requirements and edge cases

Ask about input constraints, character set, and expected behavior for cases like n=0, n greater than distinct characters in string, or empty string. Confirm that substring must be contiguous.

2. Outline approach and complexity

Propose a sliding window with two pointers and a frequency map. Explain that each character is processed at most twice, giving O(m) time where m is string length, and O(k) space where k is distinct characters.

3. Walk through algorithm steps

Describe expanding right pointer, updating frequency map, and when distinct count exceeds n, shrink from left until distinct count <= n. Track minimum length when distinct count equals n.

4. Implement the solution

Write clean code with meaningful variable names, handling edge cases upfront. Use a hash map or array for frequencies, and maintain distinct count efficiently.

5. Test with examples and discuss trade-offs

Run through provided examples and edge cases. Discuss alternative approaches (e.g., brute force) and why sliding window is optimal. Mention potential optimizations if character set is small.

Key Points to Mention

  • Sliding window technique with two pointers
  • Hash map to track character frequencies and distinct count
  • Time complexity O(m) and space complexity O(k)
  • Edge cases: n=0, n > distinct characters, empty string, no valid substring
  • Handling exactly n distinct characters: shrink when distinct > n, record when distinct == n
  • Comparison with brute force O(m^2) approach to highlight efficiency

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