Affirm·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

Affirm coding screen, one meaty string problem that took up the whole session. Felt like a decent challenge but I came in underprepared for the optimization discussion.

Questions Asked (1)

Given a list of strings, find the shortest substring for each string that doesn't appear as a substring in any other string in the list. Return None or empty if no such substring exists.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went straight to brute force: enumerate all substrings for each string, throw them into a global frequency map, then scan shortest-first for one that's unique.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints (e.g., list size, string lengths, character set) and discuss a brute-force approach first. Then propose an optimized solution using a generalized suffix automaton or suffix array to efficiently find unique substrings, and analyze time/space trade-offs.

Pro tip: Mention that you would first check for edge cases like duplicate strings or empty strings, and discuss how to handle them gracefully. Also, emphasize that you would test with small examples to validate the approach before coding.

1. Clarify requirements and constraints

Ask about input size, character set, and whether substrings must be contiguous. Confirm return format (None vs empty string) and if multiple shortest substrings exist, which to return.

2. Discuss brute-force approach

Explain generating all substrings for each string and checking against others, noting O(N^2 * L^2) time complexity. This shows baseline understanding.

3. Propose optimized solution

Describe using a generalized suffix automaton or suffix array to find unique substrings across all strings in near-linear time. Mention how to track the shortest unique substring per string.

4. Analyze trade-offs and edge cases

Compare time/space complexity of approaches, discuss handling duplicates, empty strings, and no solution cases. Suggest testing with small inputs.

Key Points to Mention

Generalized suffix automaton or suffix array for efficient substring search
Time complexity: O(total length) for optimized approach vs O(N^2 * L^2) for brute-force
Handling duplicate strings and ensuring uniqueness across all other strings
Edge cases: empty list, empty strings, no unique substring
Space complexity and memory usage for large inputs
Potential use of rolling hash for substring comparison

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