Data-driven testing: Difference between revisions

Revision as of 23:50, 23 March 2016

Revision as of 12:52, 5 April 2016

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'''Data-driven testing''' (DDT) is a term used in the testing of [[computer]] [[software]] to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. In the simplest form the tester supplies the inputs from a row in the table and expects the outputs which occur in the same row. The table typically contains values which correspond to boundary or partition input spaces. In the control methodology, test configuration is "read" from a database.

==Introduction==

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==Methodology Overview==

* '''Data-driven testing''' is the creation of test scripts to run together with their related data sets in a framework. The framework provides re-usable test logic to reduce maintenance and improve test coverage. Input and result (test criteria) data values can be stored in one or more central data sources or [[database]]s, the actual format and organisation can be implementation specific.

The data comprises variables used for both input values and output verification values. In advanced (mature) automation environments data can be harvested from a running system using a purpose-built custom tool or sniffer, the DDT framework thus performs playback of harvested data producing a powerful automated regression testing tool.

Navigation through the [[System Under Test|program]], reading of the data sources, and logging of test status and information are all coded in the test script.