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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Meta coding interview, just one problem about finding the longest repeating substring. Not much context given but it's the kind of question that sounds straightforward until you're actually in it.

Questions Asked (1)

Q1

Find the longest repeating substring in a given string.

Algorithms & Data Structures
Author's notes

This one is sneakier than it looks.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem: define 'substring' (contiguous) and 'repeating' (appears at least twice, possibly overlapping). Then present a solution using binary search on length combined with a rolling hash (Rabin-Karp) to achieve O(n log n) time, or suffix automaton for O(n) if optimal. Discuss trade-offs and handle edge cases.

Pro tip: Mention that you can use binary search on the answer because if a substring of length L repeats, then a substring of length L-1 also repeats (monotonic property). This shows deeper insight and can lead to an efficient solution.

1. Clarify the problem

Ask whether the substring must be contiguous, whether overlapping occurrences count, and what to return if no repeating substring exists. Confirm the expected time/space complexity.

2. Discuss brute force and its limitations

Mention that checking all substrings would be O(n^3) or O(n^2) with hashing, which is inefficient for large n. This sets the stage for optimization.

3. Propose an efficient approach

Explain binary search on the length of the repeating substring, using a rolling hash to check for duplicates in O(n) per length, leading to O(n log n) overall. Alternatively, mention suffix automaton or suffix array for O(n) or O(n log n) solutions.

4. Detail the algorithm

Describe how to compute rolling hashes for all substrings of a given length, store them in a hash set, and detect collisions. Discuss handling hash collisions (e.g., double hashing or verifying candidates).

5. Analyze complexity and edge cases

State time and space complexity, and discuss edge cases like empty string, no repeating substring, and all characters identical. Mention that the answer could be the entire string if it repeats.

Key Points to Mention

  • Definition of substring (contiguous) vs subsequence
  • Binary search on length due to monotonic property
  • Rolling hash (Rabin-Karp) for efficient substring comparison
  • Handling hash collisions with double hashing or verification
  • Time complexity: O(n log n) with hashing, O(n) with suffix automaton
  • Edge cases: empty string, no repeats, overlapping occurrences

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