Lesson 23: Data-Driven Testing (DDT) - Stop Hardcoding, Start Scaling
Lesson 23 introduces Data-Driven Testing (DDT) and explains why hardcoding credentials inside separate test methods is a scalability disaster. Copy-paste login tests might seem productive at first, but they tightly couple data with logic, multiplying maintenance effort every time a locator, flow, or validation rule changes. What works for five users quickly becomes unmanageable at fifty, turning small UI updates into large refactoring tasks and slowing down CI/CD cycles.
This lesson shows how separating test logic from test data allows you to scale effortlessly by adding new datasets without modifying core code. Instead of duplicating functions, you design one reusable login workflow powered by external data sources like JSON, CSV, or fixtures. Data-Driven Testing transforms repetitive scripts into structured, scalable automation that supports growth, cleaner reporting, and efficient maintenance in real production environments.
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