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

Intermediate
Apr 2026

Summary

Coding round at Uber for a frontend role. The task was building a Parking Lot system in React, and the interviewer looked like they hadn't slept in days.

Questions Asked (1)

Q1

Build a Parking Lot system using React.

System DesignTechnical Trade-offs
Author's notes

The interviewer was visibly exhausted, which made the whole thing feel a bit flat.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then outline a high-level component architecture and state management strategy. Focus on scalability, real-time updates, and trade-offs between different approaches, while demonstrating React best practices.

Pro tip: Emphasize how your design handles real-time updates and scalability, as Uber deals with high concurrency and dynamic pricing. Mention using WebSockets or server-sent events for live parking spot availability, and consider edge cases like concurrent bookings.

1. Clarify Requirements

Ask questions to understand the scope: number of floors, spots per floor, vehicle types, pricing model, real-time updates, and user roles (driver, admin).

2. Define Data Model and State

Design the data structures for parking spots, vehicles, and bookings. Decide on state management (Context, Redux, Zustand) and how to handle real-time updates.

3. Design Component Architecture

Break down the UI into reusable components: ParkingLot, Floor, Spot, Vehicle, BookingForm, etc. Consider routing and lazy loading for performance.

4. Address Scalability and Performance

Discuss optimizations: virtualized lists for large lots, memoization, code splitting, and efficient re-renders. Consider backend integration and real-time sync.

5. Discuss Trade-offs and Edge Cases

Compare approaches (e.g., optimistic UI vs. server confirmation), handle concurrency, offline support, and error states. Mention testing and accessibility.

Key Points to Mention

  • Real-time availability updates using WebSockets or polling
  • State management choice and rationale (e.g., Redux for complex state, Context for simpler)
  • Component reusability and separation of concerns
  • Performance optimizations like virtualization and memoization
  • Handling concurrent bookings and race conditions
  • Scalability considerations for large parking lots and high traffic

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