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Continuous Adaptation Management in Collective Intelligence Systems

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Software Architecture (ECSA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11681))

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Abstract

Collective Intelligence Systems (CIS), such as wikis and social networks, enable enhanced knowledge creation and sharing at organization and society levels. From our experience in R&D projects with industry partners and in-house CIS development, we learned that these platforms go through a complex evolution process. A particularly challenging aspect in this respect represents uncertainties that can appear at any time in the life-cycle of such systems. A prominent way to deal with uncertainties is adaptation, i.e., the ability to adjust or reconfigure the system in order to mitigate the impact of the uncertainties. However, there is currently a lack of consolidated design knowledge of CIS-specific adaptation and methods for managing it. To support software architects, we contribute an architecture viewpoint for continuous adaptation management in CIS, aligned with ISO/IEC/IEEE 42010. We evaluated the viewpoint in a case study with a group of eight experienced engineers. The results show that the viewpoint is well-structured, useful and applicable, and that its model kinds cover well the scope to handle different CIS-specific adaptation problems.

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Notes

  1. 1.

    http://www.alexa.com/topsites/global (last visited at 02/25/2019).

  2. 2.

    Gray shaded boxes in model kinds represent links between multiple model kinds.

References

  1. Andersson, J., et al.: Software engineering processes for self-adaptive systems. In: de Lemos, R., Giese, H., Müller, H.A., Shaw, M. (eds.) Software Engineering for Self-Adaptive Systems II. LNCS, vol. 7475, pp. 51–75. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-35813-5_3

    Chapter  Google Scholar 

  2. Corbin, J., Strauss, A.: Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 3rd edn. Sage Publications Inc., Thousand Oaks (2007)

    Google Scholar 

  3. Dorn, C., Taylor, R.N.: Coupling software architecture and human architecture for collaboration-aware system adaptation. In: Proceedings of the International Conference on Software Engineering, pp. 53–62. IEEE (2013)

    Google Scholar 

  4. Galster, M., Avgeriou, P.: A variability viewpoint for enterprise software systems. In: Proceedings of Joint WICSA/ECSA, pp. 267–271. IEEE Computer Society (2012)

    Google Scholar 

  5. Garlan, D., et al.: Rainbow: architecture-based self-adaptation with reusable infrastructure. Computer 37(10), 46–54 (2004)

    Article  Google Scholar 

  6. Hove, S.E., Anda, B.: Experiences from conducting semi-structured interviews in empirical software engineering research. In: Proceedings of the 11th IEEE International Software Metrics Symposium, pp. 23–32. IEEE Computer Society (2005)

    Google Scholar 

  7. ISO/IEC/IEEE 42010: Systems and software engineering - architecture description (2011)

    Google Scholar 

  8. Kephart, J.O., Chess, D.M.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)

    Article  MathSciNet  Google Scholar 

  9. Kramer, J., Magee, J.: Self-managed systems: an architectural challenge. In: Future of Software Engineering, pp. 259–268. IEEE Computer Society (2007)

    Google Scholar 

  10. Mahdavi-Hezavehi, S., Avgeriou, P., Weyns, D.: A classification framework of uncertainty in architecture-based self-adaptive systems with multiple quality requirements. In: Managing Trade-Offs in Adaptable Software Architectures, pp. 45–77. Morgan Kaufmann (2017)

    Google Scholar 

  11. Musil, A., Musil, J., Weyns, D., Biffl, S.: Supplementary Material: Continuous Adaptation Management in Collective Intelligence Systems (2019). http://qse.ifs.tuwien.ac.at/ci/material/pub/ecsa19/

  12. Musil, J., Musil, A., Biffl, S.: Introduction and challenges of environment architectures for collective intelligence systems. In: Weyns, D., Michel, F. (eds.) E4MAS 2014. LNCS (LNAI), vol. 9068, pp. 76–94. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23850-0_6

    Chapter  Google Scholar 

  13. Musil, J., Musil, A., Biffl, S.: SIS: an architecture pattern for collective intelligence systems. In: Proceedings of the 20th EuroPLoP, pp. 20:1–20:12. ACM (2015)

    Google Scholar 

  14. Musil, J., Musil, A., Weyns, D., Biffl, S.: An architecture framework for collective intelligence systems. In: Proceedings of the 12th WICSA, pp. 21–30. IEEE (2015)

    Google Scholar 

  15. Omicini, A., Ricci, A., Viroli, M.: Artifacts in the A&A meta-model for multi-agent Systems. Auton. Agent. Multi-Agent Syst. 17(3), 432–456 (2008)

    Article  Google Scholar 

  16. Oreizy, P., et al.: An architecture-based approach to self-adaptive software. IEEE Intell. Syst. 14(3), 54–62 (1999)

    Article  Google Scholar 

  17. Pääkkönen, P., Pakkala, D.: Reference architecture and classification of technologies, products and services for big data systems. Big Data Res. 2(4), 166–168 (2015)

    Article  Google Scholar 

  18. Dyke Parunak, H.: A survey of environments and mechanisms for human-human stigmergy. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2005. LNCS (LNAI), vol. 3830, pp. 163–186. Springer, Heidelberg (2006). https://doi.org/10.1007/11678809_10

    Chapter  Google Scholar 

  19. Ramirez, A.J., Cheng, B.H.C.: Design patterns for developing dynamically adaptive systems. In: Proceedings of the ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, pp. 49–58. ACM (2010)

    Google Scholar 

  20. Runeson, P., Host, M., Rainer, A., Regnell, B.: Case Study Research in Software Engineering: Guidelines and Examples, 1st edn. Wiley Publishing, Hoboken (2012)

    Book  Google Scholar 

  21. Saldana, J.: The Coding Manual for Qualitative Researchers, 2nd edn. Sage, Thousand Oaks (2013)

    Google Scholar 

  22. Seaman, C.B.: Qualitative methods in empirical studies of software engineering. IEEE Trans. Softw. Eng. 25(4), 557–572 (1999)

    Article  Google Scholar 

  23. Sumbaly, R., Kreps, J., Shah, S.: The “big data” ecosystem at LinkedIn. In: ACM SIGMOD Conference, pp. 1–10. ACM (2013)

    Google Scholar 

  24. Tekinerdogan, B., Sözer, H.: Variability viewpoint for introducing variability in software architecture viewpoints. In: Proceedings of the WICSA/ECSA Companion, pp. 163–166. ACM (2012)

    Google Scholar 

  25. Weyns, D.: Software engineering of self-adaptive systems. In: Cha, S., Taylor, R., Kang, K. (eds.) Handbook of Software Engineering, pp. 399–443. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-00262-6_11

    Chapter  Google Scholar 

  26. Weyns, D., Malek, S., Andersson, J.: FORMS: unifying reference model for formal specification of distributed self-adaptive systems. ACM Trans. Auton. Adapt. Syst. 7(1), 8:1–8:61 (2012)

    Article  Google Scholar 

  27. Weyns, D., et al.: On patterns for decentralized control in self-adaptive systems. In: de Lemos, R., Giese, H., Müller, H.A., Shaw, M. (eds.) Software Engineering for Self-Adaptive Systems II. LNCS, vol. 7475, pp. 76–107. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-35813-5_4

    Chapter  Google Scholar 

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Acknowledgments

The financial support by the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development is gratefully acknowledged.

Author information

Authors and Affiliations

  1. Christian Doppler Lab SQI, Institute of Information Systems Engineering, TU Wien, Vienna, Austria

    Angelika Musil, Juergen Musil & Stefan Biffl

  2. Department of Computer Science, KU Leuven, Leuven, Belgium

    Angelika Musil & Danny Weyns

  3. Department of Computer Science, Linnaeus University, Växjö, Sweden

    Danny Weyns

Authors
  1. Angelika Musil
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  2. Juergen Musil
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  3. Danny Weyns
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  4. Stefan Biffl
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Corresponding author

Correspondence to Angelika Musil .

Editor information

Editors and Affiliations

  1. Charles University, Prague, Czech Republic

    Tomas Bures

  2. University of Lille, Villeneuve d’Ascq, France

    Laurence Duchien

  3. University of L’Aquila, L’Aquila, Italy

    Paola Inverardi

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Musil, A., Musil, J., Weyns, D., Biffl, S. (2019). Continuous Adaptation Management in Collective Intelligence Systems. In: Bures, T., Duchien, L., Inverardi, P. (eds) Software Architecture. ECSA 2019. Lecture Notes in Computer Science(), vol 11681. Springer, Cham. https://doi.org/10.1007/978-3-030-29983-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-29983-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29982-8

  • Online ISBN: 978-3-030-29983-5

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