Tool support for Generating User Acceptance Tests

Autor: Camilleri, Guy, Antonelli, Leandro, Zaraté, Pascale, Gardey, Juan, Martin, Jonathan, Sakka, Amir, Torres, Diego, Fernandez, Alejandro
Přispěvatelé: Systèmes Multi-Agents Coopératifs (IRIT-SMAC), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Université Toulouse III - Paul Sabatier (UT3), Laboratorio de Investigación y Formación en Informática Avanzada [La Plata] (LIFIA), Facultad de Informática [La Plata], Universidad Nacional de la Plata [Argentine] (UNLP)-Universidad Nacional de la Plata [Argentine] (UNLP), Argumentation, Décision, Raisonnement, Incertitude et Apprentissage (IRIT-ADRIA), Facultad de Ciencias Exactas [La Plata], Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), RUC-APS — H2020-MSCA-RISE-2015/H2020-MSCA-RISE-2015, University of Zaragoza, Spain, Isabelle Linden, Alberto Turón, Fatima Dargam, Uchitha Jayawickrama, European Project: 691249,RUC-APS, Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Technologies et systèmes d'information pour les agrosystèmes (UR TSCF), Departamento de Ciencia y Tecnologia, UNQ, Argentina, Comision de Investigaciones Cientificas de la Provincia de BsAs (CICPBA), University of Zaragoza, Zarate, Pascale, Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems (www.ruc-aps.eu) - RUC-APS - 691249 - INCOMING
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: ICDSST2020
ICDSST2020, University of Zaragoza, Spain, May 2020, Zaragoza, Spain. pp.41-47
ICDSST2020, University of Zaragoza, May 2020, Zaragoza, Spain. pp.41-47
Popis: International audience; 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. This paper extends a previous paper in which 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. The proposed approach derives a Task/Method model from Scenario (through rules) and from the Task/Method model specification, all alternatives in the flow of execution are provided. 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.
Databáze: OpenAIRE
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