Optiver·Software Engineer·Onsite - Coding / Algorithms·Senior

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Apr 2026

Summary

Optiver software engineering interview with a meaty design problem centered around a balloon festival simulation. The whole thing was essentially one big class design question with a tricky physics-inspired wind model baked in. Felt more like a competitive programming problem than a typical coding round.

Questions Asked (1)

Design and implement a BalloonFestival class that tracks your team's balloons and competitor balloons across time, handles wind field updates using a cumulative altitude-based model, manages balloon stability rules with time thresholds, and returns the sorted names of your stable balloons flying at or above the highest stable competitor balloon at a given timestamp.

System DesignAlgorithms & Data StructuresData Modeling

Author's notes

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then design the data model and algorithms for each component (balloon tracking, wind updates, stability checks, and querying). Discuss trade-offs between different data structures and algorithms, and outline a high-level implementation plan before diving into details.

Pro tip: Emphasize modularity and testability: separate concerns into distinct classes or modules (e.g., Balloon, WindField, BalloonFestival) and discuss how you would unit test each part. This shows maturity and makes the design easier to extend and debug.

1. Clarify Requirements and Constraints

Ask questions to understand the expected scale (number of balloons, frequency of updates, query patterns), the exact rules for wind updates and stability, and the definition of 'highest stable competitor balloon'. Confirm assumptions about time representation and sorting order.

2. Design Data Model and Core Classes

Define classes for Balloon (with id, team, altitude, stability start time, etc.), WindField (to manage wind updates), and BalloonFestival (to coordinate). Choose appropriate data structures (e.g., hash maps for quick lookup, sorted structures for queries).

3. Implement Wind Update Logic

Model wind as a cumulative altitude-based effect: each wind update adds a delta to all balloons' altitudes based on their current altitude (e.g., wind speed proportional to altitude). Ensure updates are applied efficiently, possibly using lazy propagation or event-based updates.

4. Handle Stability Rules and Queries

Track how long each balloon has been stable (e.g., altitude unchanged for a threshold time). For a query timestamp, compute the highest stable competitor altitude, then return sorted names of your stable balloons at or above that altitude.

5. Analyze Complexity and Optimize

Discuss time and space complexity of each operation. Consider optimizations like caching query results, using balanced trees for range queries, or maintaining sorted lists incrementally. Mention potential concurrency issues if updates and queries can happen simultaneously.

Key Points to Mention

Choice of data structures (e.g., hash maps for balloon lookup, balanced trees for altitude-based queries)
Efficient handling of wind updates (e.g., lazy propagation, event-driven simulation)
Stability tracking with timestamps and thresholds (e.g., last altitude change time)
Query algorithm: finding highest stable competitor and filtering your balloons
Sorting and returning names (e.g., using a sorted set or sorting on demand)
Trade-offs between time and space complexity, and potential optimizations

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