Day 31: Unit Testing Services - Building Bulletproof AI Systems
Working Code Demo:
What We're Building Today
Today we're implementing comprehensive unit testing for our AI quiz platform's core services. You'll learn to write tests that catch bugs before they reach production, mock external dependencies like AI APIs, and achieve 80% code coverage - the industry standard that separates amateur code from production-ready systems.
Key Deliverables:
Complete unit test suite for quiz services
Mocking strategy for AI API calls
Test coverage reporting and automation
CI-ready test pipeline
Why Unit Testing Matters in AI Systems
Traditional web apps fail when users get wrong data. AI systems fail when they make wrong decisions with real consequences. Unit tests are your safety net, catching edge cases before they become user-facing disasters.
Real-World Context: When ChatGPT processes millions of requests daily, unit tests ensure each service component behaves predictably under various conditions. Your quiz platform needs the same reliability.
Component Architecture
Our testing architecture follows the Test Pyramid principle - lots of fast unit tests at the base, fewer integration tests in the middle, minimal end-to-end tests at the top.
The testing layer sits between your business logic and external dependencies, intercepting calls and providing controlled responses. This isolation lets you test complex scenarios without depending on external services.
