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Applying Self-Adaptation to Automate the Management of Online Documentation of Telecom Systems
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
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (DISA;DSIQ)ORCID iD: 0000-0003-1173-5187
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (DISA;DSIQ)ORCID iD: 0000-0002-7565-3714
Ericsson AB, Sweden.
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2018 (English)In: 14th International Conference on Automation Science and Engineering (CASE): Munich, Germany, August 20-24, 2018, IEEE, 2018, p. 1375-1380Conference paper, Published paper (Refereed)
Abstract [en]

Engineering software-intensive systems, such as production systems, is complex as these systems are subject to various types of changes that are often difficult to anticipate before deployment. Tackling this complexity requires joint expertise from different backgrounds. In this paper we focus on the problem of maintaining online technical documentation of telecom systems. In the context of continuous deployment and ever-changing user needs, high quality of the documentation of such products is in a key concern of users. To tackle this problem, different experts worked together equipping the online documentation system with a feedback loop. This feedback loop tracks changes in the system and its context and automatically adapts the documentation accordingly. The results demonstrate that this self-adaptation approach offers a viable solution to tackle the maintainability problem of online documentation of telecom systems.

Place, publisher, year, edition, pages
IEEE, 2018. p. 1375-1380
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-80973DOI: 10.1109/COASE.2018.8560502Scopus ID: 2-s2.0-85059985837ISBN: 978-1-5386-3593-3 (electronic)OAI: oai:DiVA.org:lnu-80973DiVA, id: diva2:1293940
Conference
14th International Conference on Automation Science and Engineering (CASE), Munich, Germany, August 20-24, 2018
Funder
Knowledge Foundation, 20150088Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2021-05-07Bibliographically approved

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Weyns, DannyEricsson, MorganLöwe, Welf

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CiteExportLink to record
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Citation style
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Output format
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  • asciidoc
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