BlackSeaCom 2024

FMLs comparison table

Full version for paper Waffle: A Novel Feature Modeling Language for Highly-configurable Software Systems

Approach Basic features Feature cardinality Group cardinality Cardinality combination Cardinality intervals Constraint mappint Cardinality processing Constraint-based staged configuration/validation
FDL [1] ✔ ✘ ✘ ✘ ✘ ✘ ✘ ✘
Forfamel [2] ✔ ✔ ✘ ✘ ✔ ✘ ✘ ✘
guidsl [3] ✔ ✔ ✘ ✘ ✘ ✘ ✘ ✘
VSL [4] ✔ ✔ ✘ ✘ ✘ ✘ ✘ ✘
FAMILIAR [5] ✔ ✘ ✘ ✘ ✘ ✘ ✘ ✘
TVL [6] ✔ ✔ ✔ ✘ ✘ ✘ ✘ ✘
μTVL [7] ✔ ✔ ✔ ✘ ✘ ✘ ✘ ✘
Velvet [8] ✔ ✔ ✔ ✘ ✘ ✘ ✘ ✘
PyFML [9] ✔ ✔ ✘ ✘ ✘ ✘ ✘ ✘
VM [10] ✔ ✔ ✔ ✘ ✘ ✘ ✘ ✘
FeatureIDE [11] ✔ ✘ ✘ ✘ ✘ ✘ ✘ ✘
CardyGAn [12] ✔ ✘ ✘ ✘ ✘ ✘ ✘ ✘
eMoflon [13] ✔ ✔ ✔ ✔ ✘ ✔ ✔ ✘
Clafer [14] ✔ ✔ ✘ ✘ ✘ ✘ ✘ ✘
UVL [15] ✔ ✔ ✔ ✔ ✘ ✔ ✘ ✘
Waffle ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔
  1. A. Deursen and P. Klint, “Domain-specific language design requires feature descriptions,” Journal of Computing and Information Technology, vol. 10, 01 2002.
  2. T. Asikainen, T. Männistö, and T. Soininen, “A unified conceptual foundation for feature modelling.” 01 2006, pp. 31–40.
  3. D. Batory, “Feature models, grammars, and propositional formulas,” in Software Product Lines, H. Obbink and K. Pohl, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005, pp. 7–20.
  4. A. Abele, Y. Papadopoulos, D. Servat, M. Törngren, and M. Weber, “The cvm framework - a prototype tool for compositional variability management.” 01 2010, pp. 101–105.
  5. M. Acher, P. Collet, P. Lahire, and R. B. France, “Familiar: A domain-specific language for large scale management of feature models,” Science of Computer Programming, vol. 78, no. 6, pp. 657–681, 2013.
  6. A. Classen, Q. Boucher, and P. Heymans, “A text-based approach to feature modelling: Syntax and semantics of tvl,” Science of Computer Programming, vol. 76, no. 12, pp. 1130–1143, 2011.
  7. D. Clarke, R. Muschevici, J. Proenc¸a, I. Schaefer, and R. Schlatte, “Variability modelling in the abs language,” vol. 6957, 11 2010, pp. 204–224.
  8. K. Pohl, G. Böckle, and F. Linden, Software Product Line Engineering: Foundations, Principles, and Techniques, 01 2005.
  9. A. A.F, “Pyfml - a textual language for feature modeling,” International Journal of Software Engineering and Applications, vol. 9, pp. 41–53, 01 2018.
  10. E. Alf´erez Salinas, M. Acher, J. Galindo, B. Baudry, and D. Benavides, “Modeling variability in the video domain: Language and experience report,” Software Quality Journal, vol. 27, p. 307–347, 03 2019.
  11. T. Thüm, C. Kästner, F. Benduhn, J. Meinicke, G. Saake, and T. Leich, “Featureide: An extensible framework for feature-oriented software development,” Science of Computer Programming, 01 2014.
  12. T. Schnabel, M. Weckesser, R. Kluge, M. Lochau, and A. Schürr, “Cardygan: Tool support for cardinality-based feature models.” New York, NY, USA: Association for Computing Machinery, 2016, p. 33–40.
  13. E. Leblebici, A. Anjorin, and A. Schürr, “Developing emoflon with emoflon,” in Theory and Practice of Model Transformations, D. Di Ruscio and D. Varr´o, Eds. Cham: Springer International Publishing, 2014, pp. 138–145.
  14. K. Bak, Z. Diskin, M. Antkiewicz, K. Czarnecki, and A. Wasowski, “Clafer: Unifying class and feature modeling,” Software & Systems Modeling, vol. 15, 12 2014.
  15. C. Sundermann, S. Vill, T. Thüm, K. Feichtinger, P. Agarwal, R. Rabiser, J. A. Galindo, and D. Benavides, “Uvlparser: Extending uvl with language levels and conversion strategies.” New York, NY, USA: Association for Computing Machinery, 2023, p. 39–42.