Data-Driven Testing is a software testing methodology where test scripts are designed to read input data and expected outcomes from external data sources. This approach separates test logic from test data, allowing the same test scripts to be executed with multiple sets of input data. It's a technique for improving test efficiency and coverage. Its benefits in terms of flexibility, reusability, and scalability.
If you don’t use Data-Driven Testing, the main difference is that test data is hard-coded directly inside the test scripts instead of being stored externally. This changes how tests are written, maintained, and scaled.
For example, if you have 50 different input data sets to test in a calculator application, the best approach is to use Data-Driven Testing. Instead of writing 50 separate test cases, you write one test script and execute it 50 times using different data inputs.