When to Sample from Feature Diagrams?

Nikolai KäferNikolai Käfer, Sven ApelSven Apel, Christel BaierChristel Baier, Clemens DubslaffClemens Dubslaff, Holger HermannsHolger Hermanns

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Nikolai Käfer, Sven Apel, Christel Baier, Clemens Dubslaff, Holger Hermanns
When to Sample from Feature Diagrams?
Proceedings of the 19th International Working Conference on Variability Modelling of Software-Intensive Systems, VaMoS '25, 11-20, May 2025. Association for Computing Machinery

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Projekt:Project: CPEC
Forschungsgruppe:Research Group: Algebraische und logische Grundlagen der InformatikAlgebraic and Logical Foundations of Computer Science

@inproceedings{kafer.etal_2025,
  title = {When to [[:Vorlage:Sample]] from [[:Vorlage:Feature Diagrams]]?},
  booktitle = {Proceedings of the 19th [[:Vorlage:International Working Conference]] on [[:Vorlage:Variability Modelling]] of [[:Vorlage:Software-Intensive Systems]]},
  author = {Käfer, Nikolai and Apel, Sven and Baier, Christel and Dubslaff, Clemens and Hermanns, Holger},
  year = {2025},
  month = may,
  series = {[[:Vorlage:VaMoS]] '25},
  pages = {11--20},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  doi = {10.1145/3715340.3715442},
  abstract = {Uniform random sampling (URS) has many applications in configurable systems analysis. Usually, feature models consisting of a hierarchical feature diagram and additional side constraints specify the space of valid configurations to be sampled from. However, URS has predominately been applied on feature models translated a priori into conjunctive normal form (CNF). In this work, we study URS approaches that instead operate directly on feature diagrams and provide a comparative evaluation of their performance against well-established URS tools for CNF representations. Our findings suggest that translating feature models to CNF offers advantages, even in the presence of only few side constraints.},
  isbn = {9798400714412}
}