A Modelling Approach to Generating User Acceptance Tests

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 semiautomatically 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 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. 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.

Citar como: Leandro Antonelli, Guy Camilleri, Julian Grigera, Mariangeles Hozikian, Cécile Sauvage, Pascale Zaraté, “A Modelling Approach to Generating User Acceptance Tests”, International Conference on Decision Support Systems Technologies (ICDSST 2018), Heraklion, Greece, 22/05/2018-25/05/2018, Jason Papathanosiou, P. Digkoglou, Georgios Tsaples, Fatima Dargam, Isabelle Linden (Eds.), University of Thessaloniki, 2018.

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