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TikTok·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

TikTok software engineering interview with a classic sliding window / divide-and-conquer string problem. Nothing too exotic but the follow-up complexity questions kept it from being a pure grind-and-go.

Questions Asked (1)

Q1

Given a string and an integer k, find the length of the longest substring where every distinct character appears at least k times. Walk through your algorithm, justify its correctness, analyze time and space complexity, and cover edge cases like k=1, k larger than the string length, and all-unique-character strings.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I went with divide and conquer.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem and edge cases, then present a divide-and-conquer strategy based on character counts. Explain how to recursively split the string at characters that appear fewer than k times, and analyze the complexity. Finally, discuss trade-offs and alternative approaches.

Pro tip: Mention that the divide-and-conquer approach is optimal for this problem and that a sliding window approach would be more complex due to the need to track multiple character counts. Also, proactively discuss how to handle large inputs and potential optimizations like early termination.

1. Clarify the problem and edge cases

Restate the problem in your own words and ask clarifying questions about input constraints, character set, and expected output. Discuss edge cases like k=1, k > string length, and all unique characters.

2. Outline the divide-and-conquer approach

Explain that you will count the frequency of each character in the current substring. If all characters appear at least k times, return the length. Otherwise, split the string at characters with frequency < k and recursively solve for each part.

3. Walk through an example

Choose a small example (e.g., s = 'aaabb', k = 3) and demonstrate how the algorithm splits the string and finds the longest valid substring. This shows your understanding and helps the interviewer follow.

4. Analyze complexity and justify correctness

Explain that the time complexity is O(n * alphabet size) in the worst case, but often better due to splits. Space complexity is O(alphabet size) for frequency counting and O(n) for recursion stack. Justify correctness by arguing that any valid substring cannot contain a character with frequency < k, so splitting at such characters is safe.

5. Discuss trade-offs and alternatives

Mention that a sliding window approach is possible but more complex because it requires tracking the number of characters with count >= k. Compare the divide-and-conquer approach with other methods and explain why it's suitable for this problem.

Key Points to Mention

  • Divide-and-conquer based on character frequencies
  • Recursive splitting at characters with count < k
  • Time complexity: O(n * alphabet size) worst-case, often O(n log n) or better
  • Space complexity: O(alphabet size) for frequency map, O(n) recursion stack
  • Edge cases: k=1 (entire string), k > n (0), all unique characters (0 if k>1)
  • Correctness proof: any valid substring cannot contain a character with frequency < k

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