ABSTRACT
There have been several proposals to describe the variability of software product lines by using modeling languages. In larger organizations or projects (e.g., multi product line environments) this can lead to a situation where multiple variability modeling techniques are used simultaneously. Rather than enforcing a single modeling language, we present an integrative infrastructure that provides a unified perspective for users configuring products in such multi product line environments, regardless of the different modeling methods and tools used internally. In this tool demonstration paper, we present a prototypical implementation of our framework based on Web services. So far, the prototype has been used with a feature-based, an OVM-style and a decision-oriented variability modeling approach.
- D. Benavides, S. Segura, and A. Ruiz-Cortés. Automated analysis of feature models 20 years later. Information Systems, 35(6):615--636, 2010. Google ScholarDigital Library
- G. Botterweck, M. Janota, and D. Schneeweiss. A design of a configurable feature model configurator. In 3rd International Workshop on Variability Modelling of Software-intensive Systems (VaMoS 2009), pages 165--168, Sevilla, Spain, 2009. ICB Research Report vol. 29.Google Scholar
- L. Chen, M. Babar, and N. Ali. Variability management in software product lines: A systematic review. In 13th International Software Product Line Conference (SPLC 2009), pages 81--90, San Francisco, CA, USA, 2009. ACM. Google ScholarDigital Library
- A. Classen, Q. Boucher, and P. Heymans. A text-based approach to feature modelling: Syntax and semantics of TVL. Science of Computer Programming, 76(12):1130--1143, 2011. Google ScholarDigital Library
- K. Czarnecki, P. Grünbacher, R. Rabiser, K. Schmid, and A. Wasowski. Cool features and tough decisions: a comparison of variability modeling approaches. In 6th International Workshop on Variability Modelling of Software-Intensive Systems (VaMoS 2012), pages 173--182, Leipzig, Germany, 2012. ACM. Google ScholarDigital Library
- D. Dhungana, P. Grünbacher, and R. Rabiser. The DOPLER meta-tool for decision-oriented variability modeling: A multiple case study. Automated Software Engineering, 18(1):77--114, 2011. Google ScholarDigital Library
- D. Dhungana, D. Seichter, G. Botterweck, R. Rabiser, P. Grünbacher, D. Benavides, and J. Galindo. Configuration of multi product lines by bridging heterogeneous variability modeling approaches. In 15th International Software Product Line Conference (SPLC 2011), pages 120--129, Munich, Germany, 2011. IEEE. Google ScholarDigital Library
- L. B. Lisboa, V. C. Garcia, D. L. dio, E. S. de Almeida, S. R. de Lemos Meira, and R. P. de Mattos Fortes. A systematic review of domain analysis tools. Information and Software Technology, 52(1):1--13, 2010. Google ScholarDigital Library
- K. Pohl, G. Böckle, and F. van der Linden. Software Product Line Engineering: Foundations, Principles, and Techniques. Springer, 2005. Google ScholarCross Ref
- F. Roos-Frantz, D. Benavides, A. Ruiz-Cortés, A. Heuer, and K. Lauenroth. Quality-aware analysis in product line engineering with the orthogonal variability model. Software Quality Journal, 20(3-4):519--565, 2012. Google ScholarDigital Library
- M. Sinnema and S. Deelstra. Classifying variability modeling techniques. Information and Software Technology, 49(7):717--739, 2007. Google ScholarDigital Library
- P. Trinidad, D. Benavides, A. Ruiz-Cortés, and S. S. A. Jimenez. FaMa framework. In 12th International Software Product Line Conference (SPLC 2008), vol. 2, page 359, Limerick, Ireland, 2008. Lero TR http://www.isa.us.es/fama. Google ScholarDigital Library
Index Terms
- Integrating heterogeneous variability modeling approaches with invar
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