Autor:
Markiegi, Urtzi

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umarkiegi@mondragon.edu

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Markiegi

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Urtzi

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Mondragon Goi Eskola Politeknikoa, Spain
Mondragon Unibertsitatea, Spain
Mondragon Goi Eskola Politeknikoa

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2017 - 20193
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Mostrando 1 - 3 de 3
  • Miniatura
    Artículo
    Prodevelop A Test Automation Case Study: From academic research to the real-world tool chain
    Torres, Ismael; Vos, Tanja E. J.; Markiegi, Urtzi; Calás, Ernesto; Pastor Ricos, Fernando; Etxeberria, Leire; Aldalur, Iñigo; Valencia, Xabier. Actas de las XXIV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2019), 2019-09-02.
    Prodevelop A Test Automation Case Study: From academic research to the real-world tool chain
  • Miniatura
    Artículo
    Modeling Systems Variability with Delta Rhapsody
    Perez, Xabier; Berreteaga, Oskar; Etxeberria, Leire; Arrieta, Aitor; Markiegi, Urtzi. Actas de las XXII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2017), 2017-07-19.
    Variability modeling is demanded by industrial companies to support customization of their products. However, not all the software tools include variability modeling mechanisms. IBM Rhapsody is one of the leading environments for modeling complex industrial systems. In this paper we present Delta Rhapsody, a tool for modeling variability in IBM Rhapsody models employing the delta modeling paradigm.
  • Miniatura
    Artículo
    Towards Mutation Testing of Configurable Simulink Models: a Product Line Engineering Perspective
    Arrieta, Aitor; Markiegi, Urtzi; Etxeberria, Leire. Actas de las XXII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2017), 2017-07-19.
    Mutation testing has been found to be an efficient technique in order to assess the quality of a test suite. The use of Simulink models is increasing in both industry and academia to model and simulate complex systems such as Cyber-Physical Systems (CPSs). An advantage of Simulink is its ease to integrate software and control algorithms with complex mathematical models that typically represent continuous dynamic behaviors. In addition to that, the increasing trend of industry in adopting product line engineering methods to efficiently support the variability that their products demand is resulting in configurable Simulink models. Consequently, many configurations can be employed to test the configurable system. Each of these configurations will have a set of mutants, which will be in accordance with the configuration characteristics (i.e., features). However, manually generating and configuring mutants for each of the configurations is a time-consuming and non-systematic process. To deal with this problem, we propose a methodology supported by a tool that automatically generates mutants for configurable Simulink models.