SAT–based analysis of feature models is easy

Feature models are a popular variability modeling nota-tion used in product line engineering. Automated analyses of feature models, such as consistency checking and inter-active or offline product selection, often rely on translating models to propositional logic and using satisfiability (SAT) solvers. Efficiency of individual satisfiability-based analyses has been reported previously. We generalize and quantify these studies with a series of independent experiments. We show that previously reported efficiency is not incidental. Unlike with the general SAT instances, which fall into easy and hard classes, the instances induced by feature modeling are easy throughout the spectrum of realistic models. In par-ticular, the phenomenon of phase transition is not observed for realistic feature models. Our main practical conclusion is a general encourage-ment for researchers to continued development of SAT-based methods to further exploit this efficiency in future.