With the diversity of implementation methods used across many domains and the heterogeneity of application areas, researchers and practitioners have been creating a wide range of strategies and tools to model and manage variability. We have been extending a tool-supported strategy for decision-oriented variability modeling in our own research, which is extremely adaptable to domainspecific requirements. We have already discussed the advantages of the technique and our experiences applying it in various industrial scenarios. In this study, we define the execution semantics that prefer variability models and provide a more formal description of our methodology

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