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Design an Online Coding Judge Platform

Last updated: May 11, 2026

Quick Overview

This question evaluates system design and distributed systems competencies such as scalable architecture, capacity planning, API and data modeling, secure isolation of code execution, and operational trade-off analysis for an online coding judge platform.

  • medium
  • Google
  • System Design
  • Software Engineer

Design an Online Coding Judge Platform

Company: Google

Role: Software Engineer

Category: System Design

Difficulty: medium

Interview Round: Onsite

Design an online coding practice and judging platform. The platform should let users browse programming problems, write and submit code in multiple languages, execute the code against hidden and sample test cases, receive verdicts such as accepted, wrong answer, compile error, runtime error, or time limit exceeded, and view submission history. In your design, cover: - Core functional requirements and non-functional requirements. - A minimum viable product. - Capacity estimates and bottleneck analysis. - APIs, data model, and high-level architecture. - How code execution is isolated and secured. - How to scale judging from one machine to many machines. - Trade-offs among consistency, latency, cost, and operational complexity.

Quick Answer: This question evaluates system design and distributed systems competencies such as scalable architecture, capacity planning, API and data modeling, secure isolation of code execution, and operational trade-off analysis for an online coding judge platform.

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Google logo
Google
May 2, 2026, 12:00 AM
Software Engineer
Onsite
System Design
2
0

Design an online coding practice and judging platform.

The platform should let users browse programming problems, write and submit code in multiple languages, execute the code against hidden and sample test cases, receive verdicts such as accepted, wrong answer, compile error, runtime error, or time limit exceeded, and view submission history.

In your design, cover:

  • Core functional requirements and non-functional requirements.
  • A minimum viable product.
  • Capacity estimates and bottleneck analysis.
  • APIs, data model, and high-level architecture.
  • How code execution is isolated and secured.
  • How to scale judging from one machine to many machines.
  • Trade-offs among consistency, latency, cost, and operational complexity.

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