Data-Driven Testing
Data-Driven Testing (DDT) is a software testing methodology where test scripts are designed to execute the same test logic with multiple sets of input data, typically stored in external sources like spreadsheets, databases, or CSV files. It separates test data from test logic, allowing for efficient testing of various scenarios without modifying the underlying test code. This approach is widely used in automated testing frameworks to validate application behavior across different data conditions.
Developers should use Data-Driven Testing when they need to test an application with a large volume of input data, such as validating forms, APIs, or business logic under diverse conditions. It reduces code duplication, improves test maintainability, and enhances test coverage by easily adding new test cases through data updates. Common use cases include regression testing, performance testing with varied datasets, and compliance testing where multiple data permutations are required.