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AGUTER a platform for automated generation of user acceptance tests from requirements specifications

Leandro Antonelli (LIFIA–CICPBA, Facultad de Informática, UNLP, La Plata, Argentina)
Guy Camilleri (IRIT, Université Toulouse III–Paul Sabatier, Toulouse, France)
Diego Torres (LIFIA–CICPBA, Facultad de Informática, UNLP, La Plata, Argentina) (Depto. CyT, Universidad Nacional de Quilmes, Bernal, Argentina)
Pascale Zarate (IRIT, Université Toulouse I–Capitole, Toulouse, France)


ISSN: 0368-492X

Article publication date: 10 September 2021

Issue publication date: 17 January 2023




This article proposes a strategy to make the testing step easier, generating user acceptance tests (UATs) in an automatic way from requirements artifacts.


This strategy is based on two modeling frameworks: scenarios and task/method paradigm. Scenarios are a requirement artifact used to describe business processes and requirements, and task/method paradigm is a modeling paradigm coming from the artificial intelligence field. The proposed strategy is composed of four steps. In the first step, scenarios are described through a semantic wiki website. Then scenarios are automatically translated into a task/method model (step two). In the third step, the task/method model obtained in step two is executed in order to produce and store all possible achievements of tasks and thus scenarios. The stored achievements are saved in a data structure called execution tree (ET). Finally, from this ET (step four), the UATs are generated.


The feasibility of this strategy is shown through a case study coming from the agriculture production systems field.


Generally, test design approaches deal with a small number of variables describing one specific situation where a decision table or workflow is used to design tests. The proposed approach can deal with many variables because the authors rely on scenarios that can be composed in order to obtain a tree with all the testing paths that can arise from their description.



Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS: enhancing and implementing knowledge based ICT solutions within high risk and uncertain conditions for agriculture production systems (, funded by the European Union under their funding scheme H2020-MSCA-RISE-2015


Antonelli, L., Camilleri, G., Torres, D. and Zarate, P. (2023), "AGUTER a platform for automated generation of user acceptance tests from requirements specifications", Kybernetes, Vol. 52 No. 1, pp. 44-63.



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