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Models for Self-Adaptive Systems

Published:07 September 2015Publication History

ABSTRACT

Developing self-adaptive systems has been an active research area of software engineering in the last decade. Models are so essential in building these systems that stretch their applications from design time to run time. This paper focuses on the roles of models and the relationships among them in self-adaptive systems. It classifies the types of models often required, and points out the research gaps for future investigation.

References

  1. L. Baresi, E. D. Nitto, and C. Ghezzi. Toward open-world software: Issue and challenges. volume 39, pages 36--43, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. L. Baresi, L. Pasquale, and P. Spoletini. Fuzzy goals for requirements-driven adaptation. In RE, pages 125--134, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. N. Bencomo, J. Lee, and S. O. Hallsteinsen. How dynamic is your dynamic software product line? In SPLC Workshops, pages 61--68, 2010.Google ScholarGoogle Scholar
  4. B. H. C. Cheng, P. Sawyer, N. Bencomo, and J. Whittle. A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty. In MoDELS, pages 468--483, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. S.-W. Cheng, A.-C. Huang, D. Garlan, B. R. Schmerl, and P. Steenkiste. Rainbow: Architecture-based self-adaptation with reusable infrastructure. Computer, pages 276--277, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. A. Elkhodary, N. Esfahani, and S. Malek. Fusion: a framework for engineering self-tuning self-adaptive software systems. In Proceedings of the eighteenth ACM SIGSOFT international symposium on Foundations of software engineering, FSE '10, pages 7--16, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. I. Epifani, C. Ghezzi, R. Mirandola, and G. Tamburrelli. Model evolution by run-time parameter adaptation. In Proceedings of the 31st International Conference on Software Engineering, ICSE '09, pages 111--121, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. S. Fickas and M. S. Feather. Requirements monitoring in dynamic environments. In RE, pages 140--147, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. A. Filieri, C. Ghezzi, and G. Tamburrelli. Run-time efficient probabilistic model checking. In Proceeding of the 33rd international conference on Software engineering, ICSE '11, pages 341--350, New York, NY, USA, 2011. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. C. Ghezzi, C. Menghi, A. M. Sharifloo, and P. Spoletini. On requirements verification for model refinements. In Requirements Engineering Conference (RE), 2013 21st IEEE International, pages 62--71. IEEE, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  11. C. Ghezzi, C. Menghi, A. M. Sharifloo, and P. Spoletini. On requirement verification for evolving statecharts specifications. Requirements Engineering, 19(3):231--255, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. C. Ghezzi and A. Molzam Sharifloo. Model-based verification of quantitative non-functional properties for software product lines. Inf. Softw. Technol., 55(3):508--524, Mar. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. C. Ghezzi and A. M. Sharifloo. Quantitative verification of non-functional requirements with uncertainty. In Dependable Computer Systems, pages 47--62. Springer Berlin Heidelberg, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  14. C. Ghezzi and A. ShariïňĆoo. Dealing with non-functional requirements for adaptive systems via dynamic software product-lines. 2012.Google ScholarGoogle Scholar
  15. C. Ghezzi and G. Tamburrelli. Predicting performance properties for open systems with kami. In QoSA, pages 70--85, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. L. Grunske. Specification patterns for probabilistic quality properties. In ICSE, pages 31--40, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. P. Jamshidi, A. Molzam Sharifloo, C. Pahl, and A. Metzger. Self-learning cloud controllers. In Under Review, 2015.Google ScholarGoogle Scholar
  18. D. Kim and S. Park. Reinforcement learning-based dynamic adaptation planning method for architecture-based self-managed software. International Workshop on Software Engineering for Adaptive and Self-Managing Systems, 0:76--85, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. J. Kramer and J. Magee. A rigorous architectural approach to adaptive software engineering. J. Comput. Sci. Technol., 24(2):183--188, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. B. P. Lientz and E. B. Swanson. Software Maintenance Management. Addison-Wesley Longman Publishing, Boston, MA, USA, 1980. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. P. K. McKinley, S. M. Sadjadi, E. P. Kasten, and B. H. C. Cheng. Composing adaptive software. Computer, 37:56--64, July 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. P. Oreizy, N. Medvidovic, and R. N. Taylor. Architecture-based runtime software evolution. In ICSE, pages 177--186, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. M. Salehie and L. Tahvildari. Self-adaptive software: Landscape and research challenges. TAAS, 4(2), 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. P. Sawyer, N. Bencomo, J. Whittle, E. Letier, and A. Finkelstein. Requirements-aware systems: A research agenda for re for self-adaptive systems. In RE, pages 95--103, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. A. A. Sharifloo, M. Shamsfard, Y. Motazedi, and R. Dehkharghani. An ontology for cmmi-acq model. In Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on, pages 1--6. IEEE, 2008.Google ScholarGoogle Scholar
  26. A. M. Sharifloo and P. Spoletini. Lover: light-weight formal verification of adaptive systems at run time. In Formal Aspects of Component Software, pages 170--187. Springer Berlin Heidelberg, 2013.Google ScholarGoogle ScholarCross RefCross Ref
  27. J. Whittle, P. Sawyer, N. Bencomo, B. H. C. Cheng, and J.-M. Bruel. Relax: a language to address uncertainty in self-adaptive systems requirement. Requir. Eng., 15(2):177--196, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. P. Zave and M. Jackson. Four dark corners of requirements engineering. ACM Trans. Softw. Eng. Methodol., 6(1):1--30, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. P. Zhang, W. Li, D. Wan, and L. Grunske. Monitoring of probabilistic timed property sequence charts. Softw., Pract. Exper., 41(7):841--866, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Other conferences
      ECSAW '15: Proceedings of the 2015 European Conference on Software Architecture Workshops
      September 2015
      364 pages
      ISBN:9781450333931
      DOI:10.1145/2797433

      Copyright © 2015 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 September 2015

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      • research-article
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      • Refereed limited

      Acceptance Rates

      ECSAW '15 Paper Acceptance Rate51of77submissions,66%Overall Acceptance Rate80of120submissions,67%

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