Hevo Data·Software Engineer·Onsite - Coding / Algorithms·Junior

JuniorPrefer not to say

Jul 2026

Summary

Did the machine coding round for an SDE1 role at Hevo Data. A senior engineer ran it and gave me a ride-sharing app to design. Posting here to see if anyone else has been through this recently.

Questions Asked (1)

Design a ride-sharing application in a machine coding round.

System DesignData ModelingTechnical Trade-offs

Author's notes

Got handed this and had to just start building.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the scope and core requirements (e.g., rider-driver matching, real-time tracking, fare calculation) and explicitly state your assumptions. Then design a clean, extensible object model with key classes and interfaces, and walk through the main flows (ride request, matching, trip completion) while discussing trade-offs and potential bottlenecks.

Pro tip: Focus on demonstrating clean code and separation of concerns rather than trying to build a full production system; interviewers value a working, well-structured solution that you can extend and explain clearly.

1. Clarify Requirements and Scope

Ask questions to narrow down the core features (e.g., user registration, ride matching, fare calculation, real-time updates) and non-functional requirements (scalability, concurrency). State your assumptions explicitly to set a clear boundary for the design.

2. Define Core Entities and Relationships

Identify the main objects (Rider, Driver, Ride, Location, Payment) and their attributes and relationships. Sketch a class diagram or list classes with key methods to establish a solid data model.

3. Design Key Interfaces and Services

Define interfaces for critical services like MatchingService, PricingService, and NotificationService. Explain how they interact and how you would implement them, focusing on extensibility and testability.

4. Walk Through Main Flows

Trace the end-to-end flow of a ride request: rider requests ride, system finds nearby drivers, matches one, calculates fare, updates status, and handles completion. Highlight concurrency handling and failure scenarios.

5. Discuss Trade-offs and Scalability

Explain design choices (e.g., in-memory vs. database, synchronous vs. asynchronous matching) and how you would scale the system (e.g., sharding, caching, message queues). Mention potential bottlenecks and mitigation strategies.

Key Points to Mention

Object-oriented design principles: encapsulation, inheritance, polymorphism, and design patterns (e.g., Strategy for pricing, Observer for notifications).
Data modeling: choosing appropriate data structures (e.g., geospatial index for driver locations) and database schema considerations.
Concurrency and consistency: handling simultaneous ride requests, race conditions, and ensuring data consistency.
Scalability: horizontal scaling, load balancing, and partitioning strategies for high traffic.
Trade-offs: latency vs. accuracy in matching, consistency vs. availability, and simplicity vs. extensibility.
Testing and extensibility: how to unit test core logic and add new features (e.g., ride pooling, different vehicle types) without major refactoring.

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