A Modelling Approach to Generating User Acceptance Tests
Résumé
Software testing, in particular acceptance testing, is a very important step in the development process of any application since it represents a way of matching the users’ expectations with the finished product´s capabilities. Typically considered as a cumbersome activity, many efforts have been made to alleviate the burden of writing tests by, for instance, trying to generate them automatically. However, testing still remains a largely neglected step. In this paper we propose taking advantage of existing requirement artifacts to semi-automatically generate acceptance tests. In particular, we use Scenarios, a requirement artifact used to describe business processes and requirements, and Task/Method models, a modelling approach taken from the Artificial Intelligence field. In order to generate User Acceptance tests, we propose a set of rules that allow transforming Scenarios (typically expressed in natural language), into Task/Methods that can in turn be used to generate the tests. Being high-level tests, close to the user experience, User Acceptance Tests verify that the expectations of the system are met from an end-user’s point of view. Using the proposed ideas, we show how the semi-automated generation of acceptance tests can be implemented by describing an ongoing development of a proof of concept web application designed to support the full process.
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