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Hudson River Trading·Software Engineer·Onsite - System Design / Architecture·Intermediate

Intermediate
Jun 2026

Summary

HRT system design round for a software engineer role. The focus was entirely on a data structure design problem that looked straightforward on the surface but had a lot of moving parts once you got into the implementation.

Questions Asked (1)

Q1

Given a data structure with easy-to-understand behavior but a lengthy implementation, walk through your full design process: clarifying the required operations and constraints, sketching out states and transitions, picking your core data structures, analyzing time and space complexity per operation, handling edge cases, and organizing your code and tests to reduce bugs.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

This was the whole interview basically.

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AI HintsAI Generated

Suggested Approach

Start by restating the problem and clarifying requirements, then systematically design the data structure by defining operations, states, and invariants. Walk through your choice of core data structures with complexity analysis, and finish by discussing edge cases, code organization, and testing strategy.

Pro tip: Emphasize the trade-offs between simplicity and performance, and show how you would validate your design with invariants and targeted tests. Mention that you'd start with a simple correct implementation and optimize only if needed.

1. Clarify Requirements and Constraints

Ask questions to pin down the exact operations, input ranges, performance expectations, and any memory constraints. Confirm the expected behavior for edge cases like empty structure or invalid inputs.

2. Define States and Transitions

Model the data structure's internal state and how each operation transitions between states. Identify invariants that must hold after each operation to ensure correctness.

3. Select Core Data Structures

Choose the underlying data structures (e.g., arrays, hash maps, trees) that best support the required operations. Justify your choices based on the operations' frequency and performance needs.

4. Analyze Complexity and Trade-offs

Derive time and space complexity for each operation. Discuss alternative implementations and their trade-offs, explaining why your chosen approach is optimal for the given constraints.

5. Handle Edge Cases and Organize Code

Enumerate edge cases and describe how your design handles them. Outline a modular code structure and a testing plan that covers normal, boundary, and error scenarios to reduce bugs.

Key Points to Mention

  • Clarify ambiguous requirements before designing, including operation semantics and performance targets.
  • Use invariants to reason about correctness and guide implementation.
  • Justify data structure choices with complexity analysis for each operation.
  • Discuss trade-offs between different approaches (e.g., time vs. space, simplicity vs. performance).
  • Plan for edge cases such as empty structure, duplicate elements, or invalid inputs.
  • Organize code into clear modules and write comprehensive unit tests covering all operations and edge cases.

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