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Self-adaptation of software using automatically generated control-theoretical solutions
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Catholic University of Leuven, Belgium.ORCID iD: 0000-0003-0098-9376
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
Lund University, Sweden.
2019 (English)In: Engineering adaptive software systems: communications of NII Shonan Meetings / [ed] Yijun Yu, Arosha Bandara, Shinichi Honiden, Zhenjiang Hu, Tetsuo Tamai, Hausi Muller, John Mylopoulos & Bashar Nuseibeh, Springer, 2019, p. 35-55Chapter in book (Other academic)
Abstract [en]

Control theory has contributed a set of foundational techniques to handle "change" at runtime in software applications. These techniques however have fundamental limitations as well: (i) they require the development and understanding of mathematical models; (ii) synthesizing solutions is often done on a per-problem basis, discouraging flexibility and generality. Software engineering, as a discipline, has always aimed at finding reusable and modular solutions. The combination of the desire to apply formally grounded control-theoretical principles and reuse existing solutions has motivated research on the topic of automatically generated control solutions. This research aims at designing control strategies in an automated way from data that qualifies the given problem at hand. This chapter provides an overview of the research topic of automatically generated control-theoretical solutions, explaining the key research contributions and paving the way for future research. © Springer Nature Singapore Pte Ltd. 2019. All Rights reserved.

Place, publisher, year, edition, pages
Springer, 2019. p. 35-55
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-94508DOI: 10.1007/978-981-13-2185-6_2Scopus ID: 2-s2.0-85078198507ISBN: 9789811321856 (electronic)ISBN: 9789811321849 (print)OAI: oai:DiVA.org:lnu-94508DiVA, id: diva2:1429620
Available from: 2020-05-12 Created: 2020-05-12 Last updated: 2021-04-13Bibliographically approved

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Shevtsov, StepanWeyns, Danny

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CiteExportLink to record
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