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Uniform or near-uniform generation of solutions for large satisfiability formulas is a problem of theoretical and practical interest for the testing community. Recent works proposed two algorithms (namely UniGen and QuickSampler) for reaching a good compromise between execution time and uniformity guarantees, with empirical evidence on SAT benchmarks. In the context of highly-configurable software systems (e.g., Linux), it is unclear whether UniGen and QuickSampler can scale and sample uniform software configurations. In this paper, we perform a thorough experiment on 128 real-world feature models. We find that UniGen is unable to produce SAT solutions out of such feature models. Furthermore, we show that QuickSampler does not generate uniform samples and that some features are either never part of the sample or too frequently present. Finally, using a case study, we characterize the impacts of these results on the ability to find bugs in a configurable system. Overall, our results suggest that we are not there: more research is needed to explore the cost-effectiveness of uniform sampling when testing large configurable systems.
Original languageEnglish
Title of host publicationProceedings of the 12th IEEE Conference on Software Testing, Validation and Verification
Place of PublicationXi'an, China
PublisherIEEE
Publication statusPublished - 22 Apr 2019

Publication series

NameICST '19
PublisherIEEE

ID: 50255280