Uniform and scalable sampling of highly configurable systems

Abstract Many analyses on configurable software systems are intractable when confronted with colossal and highly-constrained configuration spaces. These could instead use statistical inference, where a tractable sample accurately predicts results for the entire space. To do so, laws of inference requires each member population to be equally likely included in sample, i.e., sampling process needs “uniform”. SAT-samplers have been developed generate uniform random samples at reasonable computational cost. However, there is lack experimental validation over spaces show whether samplers indeed produce or not. This paper (i) proposes new sampler named , (ii) presents test verify uniformity, (iii) reports evaluation five other state-of-the-art samplers: . Our only satisfies both scalability uniformity.