HarveyAI·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

This was a technical screen for a Software Engineer role at HarveyAI focused on a string processing problem involving interval merging and text annotation. Pretty algorithmic for what felt like a mid-level eng interview, but the problem itself was clean and well-scoped.

Questions Asked (1)

Given a body of text and a list of source strings, wrap every exact-match occurrence of any source string in the text with highlight tags. Overlapping or adjacent matches must be merged into a single span rather than producing nested tags.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The merging part is where I had to slow down.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements and constraints first, then propose an efficient algorithm that finds all matches, merges overlapping/adjacent intervals, and applies highlights in a single pass. Discuss trade-offs between time/space complexity and implementation simplicity, and consider edge cases like multiple matches and Unicode.

Pro tip: Mention that merging intervals before applying highlights avoids nested tags and simplifies the output, and that using a single pass with a sweep-line approach can be more efficient than sorting all matches when the number of source strings is large.

1. Clarify Requirements and Constraints

Ask about input size, expected performance, handling of overlapping/adjacent matches, and whether source strings can contain special characters or be empty. Confirm the output format (e.g., HTML tags).

2. Choose an Efficient Matching Strategy

Decide between using a multi-pattern matching algorithm (e.g., Aho-Corasick) or iterating over source strings with a string search method (e.g., KMP, Boyer-Moore). Consider building a trie for efficiency if many source strings.

3. Collect and Merge Intervals

For each match, record its start and end indices. Sort intervals by start index, then merge overlapping or adjacent intervals (where next.start <= current.end).

4. Apply Highlights and Handle Edge Cases

Iterate through the merged intervals and insert highlight tags around the corresponding substrings. Handle edge cases like empty source strings, matches at the beginning/end, and Unicode characters.

5. Analyze Complexity and Trade-offs

Discuss time and space complexity of your approach, and compare with alternatives (e.g., regex-based, sorting all matches). Mention potential optimizations and limitations.

Key Points to Mention

Use of efficient multi-pattern matching algorithms like Aho-Corasick to avoid O(n*m) complexity.
Merging intervals before highlighting to prevent nested tags and ensure correct output.
Handling of overlapping and adjacent matches by merging intervals where next.start <= current.end.
Consideration of edge cases: empty source strings, matches at boundaries, Unicode, and case sensitivity.
Time and space complexity analysis of the chosen approach.
Trade-offs between simplicity (e.g., regex) and performance (e.g., custom trie-based matching).

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