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.
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