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Continuous adaptation management in collective intelligence systems
Vienna University of Technology, Austria;Catholic University of Leuven, Belgium.
Vienna University of Technology, Austria.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Catholic University of Leuven, Belgium. (DISA)ORCID iD: 0000-0002-1162-0817
Vienna University of Technology, Austria.
2019 (English)In: Software Architecture: 13th European Conference, ECSA 2019, Paris, France, September 9–13, 2019, Proceedings / [ed] Tomas Bures, Laurence Duchien & Paola Inverardi, Springer, 2019, p. 109-125Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer, 2019. p. 109-125
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11681
Keywords [en]
Adaptation, Architecture viewpoint, Collective Intelligence Systems, Life cycle, Software architecture, Collective intelligences, Complex evolutions, Design knowledge, Group of eights, Knowledge creations, Software architects, Specific adaptations, Network architecture
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-94641DOI: 10.1007/978-3-030-29983-5_8ISI: 000613130900008Scopus ID: 2-s2.0-85072837587ISBN: 9783030299828 (print)ISBN: 9783030299835 (electronic)OAI: oai:DiVA.org:lnu-94641DiVA, id: diva2:1430358
Conference
13th European Conference, ECSA 2019, Paris, France, September 9–13, 2019
Available from: 2020-05-14 Created: 2020-05-14 Last updated: 2021-05-06Bibliographically approved

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Weyns, Danny

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CiteExportLink to record
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Citation style
  • apa
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  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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