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Staged configuration of dynamic software product lines with complex binding time constraints

Published:22 January 2014Publication History

ABSTRACT

Dynamic software product lines (DSPL) constitute a promising approach for developing highly-configurable, runtime-adaptive systems in a feature-oriented way. A DSPL integrates both variability in time and space in a unified conceptual framework. For this, domain features are equipped with additional binding time information to distinguish between static configuration parameters and dynamically (re-) configurable features. Until now, little support exists to specify and validate staged (re-)configuration semantics for DSPLs in a concise way. In this paper, we propose conservative extensions to domain feature models comprising variable feature binding times together with different kinds of binding time constraints. Those extensions are motivated by a real-world industrial case study from the automation engineering domain. Our implementation performs a model transformation into plain feature models treatable by corresponding state-of-the-art analysis tools. We conducted an evaluation of our approach concerning the case study.

References

  1. D. Batory. Feature models, grammars, and propositional formulas. In SPLC'05, pages 7--20, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. D. Benavides, P. Trinidad, and A. Ruiz-Cortés. Automated reasoning on feature models. In CAiSE, pages 491--503, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Classen, A. Hubaux, and P. Heymans. A Formal Semantics for Multi-level Staged Configuration. In VaMoS'09, pages 51--60, 2009.Google ScholarGoogle Scholar
  4. K. Czarnecki, S. Helsen, and U. Eisenecker. Staged configuration through specialization and multi-level configuration of feature models. Software Process: Improvement and Practice, 10(2):143--169, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  5. K. Czarnecki, S. Helsen, and E. Ulrich. Staged Configuration Using Feature Models. In SPLC'04, pages 266--283, 2004.Google ScholarGoogle Scholar
  6. S. Hallsteinsen, M. Hinchey, S. Park, and K. Schmid. Dynamic software product lines. Computer, 41:93--95, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Heidelberg University Hospital. Heidelberg Ion-Beam Therapy Center. http://www.klinikum.uni-heidelberg.de/, 2013.Google ScholarGoogle Scholar
  8. M. Helvensteijn. Dynamic delta modeling. In SPLC'12, pages 127--134. ACM, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. A. Hubaux, A. Classen, and P. Heymans. Formal modelling of feature configuration workflows. In SPLC'09, pages 221--230, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. K. C. Kang, S. G. Cohen, J. A. Hess, W. E. Novak, and S. A. Peterson. Feature Oriented Domain Analysis (FODA). Technical report, CMU, 1990.Google ScholarGoogle Scholar
  11. A. S. Karataş, H. Oğuztüzün, and A. Doğru. Mapping extended feature models to constraint logic programming over finite domains. In SPLC'10, pages 286--299. Springer, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. H. Mei, W. Zhang, and F. Gu. A feature oriented approach to modeling and reusing requirements of software product lines. In COMPSAC '03, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. L. T. Passos, T. Berger, M. Novakovic, K. Czarnecki, Y. Xiong, and A. Wasowski. A study of non-boolean constraints in variability models of an embedded operating system. In SPLC'11, pages 21--28, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. K. Pohl, G. Böckle, and F. van der Linden. Software Product Line Engineering: Foundations, Principles and Techniques. Springer, 2005. Google ScholarGoogle ScholarCross RefCross Ref
  15. M. Rosenmüller, N. Siegmund, G. Saake, and S. Apel. Code generation to support static and dynamic composition of software product lines. In 7th GPCE, pages 3--12. ACM, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. K. Saller, M. Lochau, and I. Reimund. Context-aware dspls: model-based runtime adaptation for resource-constrained systems. In SPLC'13, pages 106--113. ACM, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. T. Thüm, C. Kästner, S. Erdweg, and N. Siegmund. Abstract features in feature modeling. In In SPLC'11, pages 191--200, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. J. White, B. Dougherty, D. C. Schmidt, and D. Benavides. Automated reasoning for multi-step feature model configuration problems. In SPLC'09, pages 11--20, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

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            cover image ACM Other conferences
            VaMoS '14: Proceedings of the 8th International Workshop on Variability Modelling of Software-Intensive Systems
            January 2014
            170 pages
            ISBN:9781450325561
            DOI:10.1145/2556624

            Copyright © 2014 ACM

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            New York, NY, United States

            Publication History

            • Published: 22 January 2014

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            VaMoS '14 Paper Acceptance Rate21of55submissions,38%Overall Acceptance Rate66of147submissions,45%

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