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Evaluating state-of-the-art # SAT solvers on industrial configuration spaces

Authors:

Chico Sundermann,

Paul Maximilian Bittner,

Jeffrey M. Young,

Ina SchaeferAuthors Info & Claims

Empirical Software Engineering, Volume 28, Issue 2

https://doi.org/10.1007/s10664-022-10265-9

Published: 13 January 2023 Publication History

Abstract

Product lines are widely used to manage families of products that share a common base of features. Typically, not every combination (configuration) of features is valid. Feature models are a de facto standard to specify valid configurations and allow standardized analyses on the variability of the underlying system. A large variety of such analyses depends on computing the number of valid configurations. To analyze feature models, they are typically translated to propositional logic. This allows to employ # SAT solvers that compute the number of satisfying assignments of the propositional formula translated from a feature model. However, the # SAT problem is generally assumed to be even harder than SAT and its scalability when applied to feature models has only been explored sparsely. Our main contribution is an investigation of the performance of off-the-shelf # SAT solvers on computing the number of valid configurations for industrial feature models. We empirically evaluate 21 publicly available # SAT solvers on 130 feature models from 15 subject systems. Our results indicate that current solvers master a majority of the evaluated systems (13/15) with the fastest solvers requiring less than one second for each successfully evaluated feature model. However, there are two complex systems for which none of the evaluated solvers scales. For the given experiment design, the solvers that consumed the least runtime are sharpSAT (2.5 seconds in sum for the 13 systems) and Ganak (3.5 seconds).

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Cited By

Bittner PSchultheiß AMoosherr BYoung JTeixeira LWalkingshaw EAtaei PThüm T(2024)On the Expressive Power of Languages for Static VariabilityProceedings of the ACM on Programming Languages10.1145/36897478:OOPSLA2(1018-1050)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689747
Bittner PSchultheiß AMoosherr BKehrer TThüm Td'Amorim M(2024)Variability-Aware Differencing with DiffDetectiveCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663813(632-636)Online publication date: 10-Jul-2024
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Bombarda AGargantini A(2024)On the Use of Multi-valued Decision Diagrams to Count Valid Configurations of Feature ModelsProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3672594(96-106)Online publication date: 2-Sep-2024
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Evaluating state-of-the-art # SAT solvers on industrial configuration spaces
1. General and reference
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2. Software and its engineering

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cover image Empirical Software Engineering

Empirical Software Engineering Volume 28, Issue 2

Mar 2023

1389 pages

ISSN:1382-3256

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© The Author(s) 2023.

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Kluwer Academic Publishers

United States

Publication History

Published: 13 January 2023

Accepted: 25 November 2022

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Deutsche Forschungsgemeinschaft
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Cited By

Bittner PSchultheiß AMoosherr BYoung JTeixeira LWalkingshaw EAtaei PThüm T(2024)On the Expressive Power of Languages for Static VariabilityProceedings of the ACM on Programming Languages10.1145/36897478:OOPSLA2(1018-1050)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3689747
Bittner PSchultheiß AMoosherr BKehrer TThüm Td'Amorim M(2024)Variability-Aware Differencing with DiffDetectiveCompanion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering10.1145/3663529.3663813(632-636)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3663529.3663813
Bombarda AGargantini A(2024)On the Use of Multi-valued Decision Diagrams to Count Valid Configurations of Feature ModelsProceedings of the 28th ACM International Systems and Software Product Line Conference10.1145/3646548.3672594(96-106)Online publication date: 2-Sep-2024
https://dl.acm.org/doi/10.1145/3646548.3672594
Heß TSchmidt TOstheimer LKrieter SThüm T(2024)UnWise: High T-Wise Coverage from Uniform SamplingProceedings of the 18th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3634713.3634716(37-45)Online publication date: 7-Feb-2024
https://dl.acm.org/doi/10.1145/3634713.3634716
Horcas JBallesteros JPinto MFuentes L(2023)Elimination of constraints for parallel analysis of feature modelsProceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A10.1145/3579027.3608981(99-110)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1145/3579027.3608981
Eichhorn DPett TOsborne TSchaefer I(2023)Quantum Computing for Feature Model AnalysisProceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A10.1145/3579027.3608971(1-7)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1145/3579027.3608971
Sundermann CKuiter EHeß TRaab HKrieter SThüm T(2023)On the benefits of knowledge compilation for feature-model analysesAnnals of Mathematics and Artificial Intelligence10.1007/s10472-023-09906-692:5(1013-1050)Online publication date: 6-Nov-2023
https://dl.acm.org/doi/10.1007/s10472-023-09906-6

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