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Hudson River Trading·Software Engineer·Online Assessment (OA)·Intermediate

Intermediate
Jun 2026

Summary

HRT OA for a software engineering role. The whole thing was weirdly open-ended in a way I wasn't expecting, less about solving a specific problem and more about whether you actually know how to think about testing rigorously.

Questions Asked (1)

Q1

You're given an online assessment with almost no sample test cases and told to write your own. How do you design a thorough set of tests? Walk through your edge-case categories, how you generate inputs and expected outputs, how you validate against a reference solution, and how you know when you've tested enough.

Algorithms & Data StructuresTechnical Trade-offsAdaptability & Ambiguity
Author's notes

This is the kind of question that sounds manageable until you actually try to answer it without hand-waving.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem constraints and requirements, then systematically design tests covering edge cases, normal cases, and performance. Explain how you generate inputs and expected outputs, validate against a reference solution, and use coverage metrics and mutation testing to decide when to stop.

Pro tip: Emphasize that writing tests is not just about finding bugs but also about understanding the problem deeply; mention that you prioritize tests based on risk and likelihood of failure, and that you automate test generation where possible to save time.

1. Understand the Problem and Constraints

Identify input types, output format, constraints (size, time, memory), and any special conditions. Clarify ambiguities before designing tests.

2. Categorize Edge Cases

List categories such as empty input, single element, maximum/minimum values, duplicates, sorted/reverse-sorted, negative numbers, overflow, and invalid inputs.

3. Generate Inputs and Expected Outputs

Create inputs manually for small cases and use a reference solution (brute force or known correct implementation) to generate expected outputs for larger cases. Consider random and adversarial input generation.

4. Validate Against a Reference Solution

Implement a simple, obviously correct solution (e.g., brute force) to cross-check outputs. Use differential testing: compare your optimized solution against the reference on many random inputs.

5. Know When to Stop

Use coverage metrics (branch, path), mutation testing, and risk analysis to determine test adequacy. Stop when additional tests no longer reveal new failures or when coverage targets are met.

Key Points to Mention

  • Boundary value analysis and equivalence partitioning
  • Randomized testing with a reference solution (differential testing)
  • Performance testing with large inputs to check time/memory limits
  • Handling invalid or unexpected inputs (robustness)
  • Using code coverage and mutation testing to assess test suite quality
  • Prioritizing tests based on risk and likelihood of bugs

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