What do we call an approximation of a testing result that can be used despite incomplete input data?

The term used to describe an approximation of a testing result that can be utilized even when the input data is incomplete is known as test estimation. Test estimation involves predicting the time, effort, and resources required to perform testing activities based on available information and expert judgment. It is essential in agile environments where requirements and inputs may be changing frequently, allowing teams to plan and allocate resources effectively despite uncertainty.

In agile testing, test estimation helps foster agility and adaptability. It provides teams with a means to discuss and agree upon the testing strategy even when they do not have all the details at hand. This fosters collaborative planning and encourages ongoing communication among team members to adjust estimates as more information becomes available.

Other terms in this context refer to different concepts: a test charter pertains to the scope and objectives of a testing session, a test condition specifies what needs to be tested (understandably a more detailed focus), and test data preparation involves creating or identifying the necessary data for testing, which is distinct from estimations regarding outcomes. Each of these plays a role in the testing process, but none serve the purpose of approximating a result based on incomplete data as effectively as test estimation does.