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rippling·Software Engineer·Take-home Assignment·Intermediate

Intermediate
May 2026

Summary

Rippling gave me a take-home to build a mini Q&A REST API, basically a stripped-down Stack Overflow clone. Solid task, not too flashy, but there's more surface area than it looks at first glance.

Questions Asked (1)

Q1

Build a REST API for a Stack Overflow-style Q&A system. It should support creating questions, listing questions, fetching a question by ID, posting answers, listing answers per question, and a basic search feature. Any language or framework is fine. Make sure to cover the data model, request validation, error handling, and write some tests.

API & IntegrationsData ModelingSystem Design
Author's notes

More involved than I expected.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints (e.g., expected scale, authentication, search semantics) before diving into design. Then outline a clean layered architecture: data model, API endpoints, validation, error handling, and tests. Walk through each layer with concrete examples, emphasizing trade-offs and best practices.

Pro tip: Demonstrate production-readiness by discussing pagination, rate limiting, and idempotency for POST endpoints—these show you think beyond the happy path. Also, mention how you'd version the API and handle backward compatibility.

1. Clarify Requirements and Scope

Ask about expected traffic, authentication, search complexity (full-text vs. simple), and whether answers need voting or comments. This shows you avoid over-engineering and align with business needs.

2. Design the Data Model

Define entities: Question (id, title, body, tags, created_at, updated_at), Answer (id, question_id, body, created_at, updated_at). Discuss indexes on foreign keys and search fields, and consider soft deletes for auditability.

3. Define API Endpoints and Contracts

List RESTful routes: POST /questions, GET /questions (with pagination), GET /questions/{id}, POST /questions/{id}/answers, GET /questions/{id}/answers, GET /search?q=. Specify request/response schemas, status codes, and content types.

4. Implement Validation and Error Handling

Use a validation library or custom middleware to check required fields, length limits, and data types. Return consistent error responses with appropriate HTTP status codes (400, 404, 422, 500) and error codes/messages.

5. Write Tests and Discuss Deployment

Cover unit tests for validation and business logic, integration tests for endpoints (including error cases), and mention how you'd run tests in CI. Briefly touch on deployment (e.g., Docker, environment variables) and monitoring.

Key Points to Mention

  • Use of pagination (limit/offset or cursor-based) for listing questions and answers to handle large datasets.
  • Input validation: sanitize inputs, enforce max lengths, validate foreign keys (e.g., question exists before posting answer).
  • Error handling: consistent JSON error format, proper HTTP status codes, and logging for debugging.
  • Search implementation: simple LIKE queries vs. full-text search (e.g., PostgreSQL tsvector, Elasticsearch) and trade-offs.
  • Testing strategy: unit tests for models/validators, integration tests for API endpoints, and mocking external dependencies.
  • API versioning and documentation (e.g., OpenAPI/Swagger) for maintainability and client integration.

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