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HarveyAI·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Interviewed for a software engineer role at HarveyAI and got a spreadsheet-style coding problem, reminded me of something I'd seen on LeetCode before. Pretty focused on data structure choices more than anything else.

Questions Asked (1)

Q1

Implement setCell and getCell functions for a spreadsheet. No formula support, just integer values. What data structure would you use?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The interviewer kept pushing back on my first instinct and asked me to justify why I picked what I picked.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements: sparse vs. dense data, expected operations, and memory constraints. Then propose a hash map (dictionary) keyed by cell coordinates, explaining why it's efficient for sparse data and simple to implement. Finally, discuss trade-offs with alternatives like 2D arrays and when each might be appropriate.

Pro tip: Mention that in a real spreadsheet, most cells are empty, so a sparse representation like a hash map is often preferred. Also, consider using a composite key (e.g., tuple or string) and discuss potential memory overhead.

1. Clarify Requirements

Ask about expected data density, typical operations, and memory constraints to determine if a sparse or dense structure is better.

2. Propose Primary Data Structure

Suggest a hash map (dictionary) with cell coordinates as keys and integer values as values, explaining its O(1) average time for get/set.

3. Discuss Alternatives and Trade-offs

Compare with a 2D array (dense, O(1) access but memory-heavy for sparse data) and mention hybrid approaches if needed.

4. Address Edge Cases and Implementation Details

Cover key design (e.g., tuple vs. string), handling out-of-bounds, default values, and potential memory optimizations.

Key Points to Mention

  • Hash map provides O(1) average time for getCell and setCell.
  • Sparse data is common in spreadsheets, so a hash map saves memory compared to a 2D array.
  • 2D array is simpler and faster for dense data but wastes memory if sparse.
  • Composite key design: use a tuple (row, col) or a string like 'A1' for readability.
  • Consider thread safety if concurrent access is expected.
  • Discuss memory overhead of hash maps (e.g., load factor, resizing).

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