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Applications of #SAT Solvers on Feature Models

Authors:

Chico Sundermann,

Paul M. Bittner,

Ina SchaeferAuthors Info & Claims

VaMoS '21: Proceedings of the 15th International Working Conference on Variability Modelling of Software-Intensive Systems

Article No.: 12, Pages 1 - 10

https://doi.org/10.1145/3442391.3442404

Published: 09 February 2021 Publication History

Abstract

Product lines are ubiquitous for managing variable systems. The variability of a product line is typically described in terms of a feature model. Analyzing a feature model gives insight into various aspects, such as the validity of a configuration of features. Several analyses have been considered that require computing the number of valid configurations which proves highly inefficient when using regular SAT solvers. A #SAT solver computes the number of satisfying variable assignments of a propositional formula and is specifically optimized for the aforementioned analyses. In this work, we summarize and unify the state-of-the-art on #SAT-based feature-model analyses and propose a variety of new #SAT-based analyses. We provide an exhaustive catalogue for applications of #SAT for feature models serving as a reference for researchers and practitioners. Furthermore, we show that all these 21 applications are based on only three different #SAT queries. Thus, future research can focus on providing solutions and optimizations for those three queries to accelerate #SAT-based applications.

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Cited By

Horcas JBurgueño LKienzle J(2025)Leveraging belief uncertainty for informed decision making in software product line evolutionJournal of Systems and Software10.1016/j.jss.2024.112235219:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.jss.2024.112235
Sundermann CLoth JThüm TFilkov VRay BZhou M(2024)Efficient Slicing of Feature Models via Projected d-DNNF CompilationProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695594(1332-1344)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695594
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
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VaMoS '21: Proceedings of the 15th International Working Conference on Variability Modelling of Software-Intensive Systems

February 2021

150 pages

ISBN:9781450388245

DOI:10.1145/3442391

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 09 February 2021

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VaMoS'21

VaMoS'21: 15th International Working Conference on Variability Modelling of Software-Intensive Systems

February 9 - 11, 2021

Krems, Austria

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Horcas JBurgueño LKienzle J(2025)Leveraging belief uncertainty for informed decision making in software product line evolutionJournal of Systems and Software10.1016/j.jss.2024.112235219:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.jss.2024.112235
Sundermann CLoth JThüm TFilkov VRay BZhou M(2024)Efficient Slicing of Feature Models via Projected d-DNNF CompilationProceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering10.1145/3691620.3695594(1332-1344)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3691620.3695594
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
Sundermann CRaab HHeß TThüm TSchaefer I(2024)Reusing d-DNNFs for Efficient Feature-Model CountingACM Transactions on Software Engineering and Methodology10.1145/368046533:8(1-32)Online publication date: 30-Jul-2024
https://dl.acm.org/doi/10.1145/3680465
Zeyen OCordy MPerrouin GAcher MRoychoudhury APaiva AAbreu RStorey M(2024)Exploring the Computational Complexity of SAT Counting and Uniform Sampling with Phase TransitionsProceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings10.1145/3639478.3643097(322-323)Online publication date: 14-Apr-2024
https://dl.acm.org/doi/10.1145/3639478.3643097
Güthing LBittner PSchaefer IThüm T(2024)Explaining Edits to Variability Annotations in Evolving Software Product LinesProceedings of the 18th International Working Conference on Variability Modelling of Software-Intensive Systems10.1145/3634713.3634725(93-102)Online publication date: 7-Feb-2024
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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
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Burgueño LHorcas JKienzle J(2023)Development and Evolution of Software Product Lines Driven by Stakeholder BeliefsProceedings of the 27th ACM International Systems and Software Product Line Conference - Volume A10.1145/3579027.3608975(34-40)Online publication date: 28-Aug-2023
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Ghallab KZiadi TChalal Z(2023)Migrating Individual Applications into Software Product Lines Using the Mobioos Forge Platform2023 30th Asia-Pacific Software Engineering Conference (APSEC)10.1109/APSEC60848.2023.00060(483-492)Online publication date: 4-Dec-2023
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Sundermann CHeß TNieke MBittner PYoung JThüm TSchaefer I(2023)Evaluating state-of-the-art # SAT solvers on industrial configuration spacesEmpirical Software Engineering10.1007/s10664-022-10265-928:2Online publication date: 13-Jan-2023
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