A data-driven framework is a software testing methodology or design pattern where test cases are executed using test data stored separately from the test logic itself.
It is used to drive test cases and suites from an external data feed. This means that the actual test script or code remains constant, while different sets of input and output data are supplied from an external source to run the test multiple times. This approach significantly enhances test coverage and efficiency by allowing a single test script to be reused with various data inputs.
Key Characteristics
At the core of a data-driven framework are several distinct characteristics:
- Separation of Data and Code: This is a fundamental principle. As mentioned in the reference, a Data Driven Framework in Selenium is a technique of separating the “data set” from the actual “test case” (code). The test logic (how the test performs actions) is kept separate from the data it uses (what values are input, what results are expected).
- External Data Storage: Test data is stored in external files or databases.
- Variety of Data Sources: The external data feed can come from various structured sources. Commonly used sources include data sheets like xls, xlsx, and csv files, as highlighted in the reference. Other sources might include XML files, databases, or even plain text files.
- Test Case Driving: The data stored externally "drives" or controls the execution of the test cases, providing the necessary inputs and verification points for each iteration.
Why Use a Data-Driven Framework?
Adopting a data-driven approach offers several practical advantages for software testing:
- Increased Test Coverage: Easily execute test cases with a wide range of data inputs without writing new scripts for each data set.
- Improved Maintainability: When test data changes, you only need to update the external data source, not the test code itself.
- Reduced Redundancy: Avoid duplicating test logic across multiple scripts that only differ by the data they use.
- Enhanced Collaboration: Data files can often be managed and reviewed by non-technical stakeholders, facilitating better collaboration between teams.
- Easier Test Creation: Once the framework is set up, creating new tests or test scenarios often just involves adding new rows or columns to the data file.
By externalizing the data used in tests, data-driven frameworks provide a flexible and scalable way to perform comprehensive testing, especially in scenarios requiring testing with numerous different data combinations.
