Uber·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

Jun 2026

Summary

Uber coding round that was framed as OO Design rather than a pure algorithm problem. Just the one question but it went in a direction I wasn't fully prepared for.

Questions Asked (1)

Design a parking lot system using object-oriented principles.

System DesignTechnical Trade-offs

Author's notes

Went in expecting LeetCode-style problems and got hit with OO Design instead.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (e.g., multiple floors, vehicle types, payment) and then design a class hierarchy with core entities like ParkingLot, Level, ParkingSpot, and Vehicle. Focus on extensibility and key operations like parking and unparking, discussing trade-offs in data structures and concurrency.

Pro tip: Demonstrate awareness of real-world constraints by discussing how to handle concurrent access to spots and how to scale the design for high throughput, as Uber deals with large-scale systems.

1. Clarify Requirements

Ask questions to understand scope: number of levels, vehicle types (car, bike, truck), payment methods, entry/exit points, and whether reservations are needed.

2. Identify Core Entities

Define main classes such as ParkingLot, Level, ParkingSpot, Vehicle, Ticket, and Payment, and their relationships (e.g., ParkingLot has Levels, Level has Spots).

3. Design Class Interfaces

Specify key methods for each class, e.g., ParkingLot.parkVehicle(vehicle), unparkVehicle(ticket), and ParkingSpot.isAvailable(), ensuring separation of concerns.

4. Implement Key Operations

Detail algorithms for parking (finding an available spot) and unparking (calculating fee), considering data structures like maps or lists for efficient lookup.

5. Discuss Trade-offs and Extensions

Talk about design choices (e.g., spot allocation strategy, concurrency handling) and potential extensions like electric vehicle charging or dynamic pricing.

Key Points to Mention

Use of inheritance and polymorphism for vehicle types and spot types.
Strategy pattern for different spot allocation algorithms (e.g., nearest spot).
Concurrency control mechanisms (e.g., locks, atomic operations) to handle simultaneous parking attempts.
Scalability considerations: sharding by level or using distributed locks for large parking lots.
Payment integration and ticket generation for tracking sessions.
Extensibility for future requirements like valet parking or EV charging.

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