Uniform Sampling of SAT Solutions for Configurable Systems

Uniform Sampling of SAT Solutions for Configurable Systems: Are We There Yet?

Plazar, Quentin (Inria; Université de Rennes)
Acher, Mathieu (Université de Rennes; Inria)
Perrouin, Gilles (University of Namur)
Devroey, Xavier (TU Delft Software Engineering)
Cordy, Maxime (University of Luxembourg)

O'Conner, L. (editor)

2019

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.

Configurable-systems
SAT
Software-product-lines
Software-testing
Uniform-sampling
Variability-modeling

http://resolver.tudelft.nl/uuid:f568f332-8fa8-4b79-8b90-304b063bfb94

https://doi.org/10.1109/ICST.2019.00032

IEEE, Piscataway, NJ

978-1-7281-1737-9

Proceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation, ICST 2019: Proceedings

ICST 2019, 2019-04-22 → 2019-04-27, Xi'an, China

Accepted author manuscript

Institutional Repository

conference paper

© 2019 Quentin Plazar, Mathieu Acher, Gilles Perrouin, Xavier Devroey, Maxime Cordy