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Berrios, Mario

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i12bercm@uco.es
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Berrios
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Mario
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University of Córdoba, Spain
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    Artículo
    Contrastive and counterfactual explanations for test case prioritization: Ideas and challenges
    Ramírez, Aurora; Berrios, Mario; Feldt, Robert; Romero, José Raúl. Actas de las XXVII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2023), 2023-09-12.
    As machine learning (ML) is increasingly used in software engineering (SE), explainable artificial intelligence (XAI) is crucial for understanding choices made by opaque, "black-box" models. Test case prioritization (TCP) is an important SE problem that can benefit from ML. In this paper, we explore two approaches for generating explanations in ML-based TCP, contrastive and counterfactual XAI, and present application scenarios where they can enhance testers' comprehension of model outputs. Specifically, we use DiCE, a method for generating counterfactual explanations, as an illustrative example and conclude by discussing open issues.