Artículos (Lenguajes y Sistemas Informáticos)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11392

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Examinando Artículos (Lenguajes y Sistemas Informáticos) por Agencia financiadora "Austrian Research Promotion Agency"

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    DirectDebug: A software package for the automated testing and debugging of feature models
    (Elsevier, 2021) Le, Viet-Man; Felfernig, Alexander; Tran, Thi Ngoc Trang; Atas, Müslüm; Uta, Mathias; Benavides Cuevas, David Felipe; Galindo Duarte, José Ángel; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Austrian Research Promotion Agency; Ministerio de Economía y Competitividad (MINECO). España
    Complex and large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we propose the DirectDebug algorithm that supports the automated testing and debugging of variability models. Our approach assists software engineers in identifying an adaptation hint (diagnosis) that makes all test cases consistent with the knowledge base. We also develop the software package so-called d2bug_eval to evaluate the DirectDebug’s performance. The software package can be re-produced thoroughly to evaluate consistency-based algorithms.
  • Miniatura
    Acceso AbiertoArtículo
    DirectDebug: Automated Testing and Debugging of Feature Models
    (Cornell University, 2021) Le, Viet-Man; Felfernig, Alexander; Uta, Mathias; Benavides Cuevas, David Felipe; Galindo Duarte, José Ángel; Tran, Thi Ngoc Trang; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; European Union (UE); Austrian Research Promotion Agency; Ministerio de Economía y Competitividad (MINECO). España
    Variability models (e.g., feature models) are a common way for the representation of variabilities and commonalities of software artifacts. Such models can be translated to a logical representation and thus allow different operations for quality assurance and other types of model property analysis. Specifically, complex and often large-scale feature models can become faulty, i.e., do not represent the expected variability properties of the underlying software artifact. In this paper, we introduce DIRECTDEBUG which is a direct diagnosis approach to the automated testing and debugging of variability models. The algorithm helps software engineers by supporting an automated identification of faulty constraints responsible for an unintended behavior of a variability model. This approach can significantly decrease development and maintenance efforts for such models.