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Perpetual assurances for self-adaptive systems
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Katholieke Universiteit Leuven, Belgium.ORCID iD: 0000-0002-1162-0817
Aston University, UK.
University of York, UK.
Carnegie Mellon University, USA.
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2017 (English)In: Software Engineeringfor Self-Adaptive Systems III, Assurances: International SeminarDagstuhl Castle, Germany, December 15–19, 2013Revised Selected and Invited Papers123 / [ed] Rogério de Lemos, David Garlan Carlo Ghezzi, Holger Giese, Springer, 2017, p. 31-63Chapter in book (Refereed)
Abstract [en]

Providing assurances for self-adaptive systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the self-adaptive system complies with its requirements calls for an enduring process spanning the whole lifetime of the system. In this process, humans and the system jointly derive and integrate new evidence and arguments, which we coined perpetual assurances for self-adaptive systems. In this paper, we provide a background framework and the foundation for perpetual assurances for self-adaptive systems. We elaborate on the concrete challenges of offering perpetual assurances, requirements for solutions, realization techniques and mechanisms to make solutions suitable. We also present benchmark criteria to compare solutions. We then present a concrete exemplar that researchers can use to assess and compare approaches for perpetual assurances for self-adaptation. © Springer International Publishing AG 2017.

Place, publisher, year, edition, pages
Springer, 2017. p. 31-63
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 9640
Keywords [en]
Concretes, Software engineering, Incomplete knowledge, Self adaptation, Self-adaptive system, Sensor noise, Adaptive systems
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-86314DOI: 10.1007/978-3-319-74183-3_2Scopus ID: 2-s2.0-85041863959ISBN: 9783319741826 (print)ISBN: 9783319741833 (electronic)OAI: oai:DiVA.org:lnu-86314DiVA, id: diva2:1337029
Conference
International Seminar on Software Engineering for Self-Adaptive Systems: Assurances, 15-19 December 2013
Note

Conference code: 210089; Export Date: 11 June 2019; Conference Paper

Available from: 2019-07-11 Created: 2019-07-11 Last updated: 2019-09-02Bibliographically approved

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Weyns, Danny

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  • apa
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