Preliminary Results of a Survey on the Use of Self-Adaptation in Industry

Danny Weyn, Ilias Gerostathopoulos, Nadeem Abbas, Jesper Andersson, Stefan Biffl, Premek Brada, Tomas Bures, Amleto Di Salle, Patricia Lago, Angelika Musil, Juergen Musil, Patrizio Pelliccione

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Abstract

Self-Adaptation equips a software system with a feedback loop that automates tasks that otherwise need to be performed by operators. Such feedback loops have found their way to a variety of practical applications, one typical example is an elastic cloud. Yet, the state of the practice in self-Adaptation is currently not clear. To get insights into the use of self-Adaptation in practice, we are running a largescale survey with industry. This paper reports preliminary results based on survey data that we obtained from 113 practitioners spread over 16 countries, 62 of them work with concrete self-Adaptive systems. We highlight the main insights obtained so far: motivations for self-Adaptation, concrete use cases, and difficulties encountered when applying self-Adaptation in practice. We conclude the paper with outlining our plans for the remainder of the study.

Original languageEnglish
Title of host publication2022 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)
Subtitle of host publication[Proceedings]
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages70-76
Number of pages7
ISBN (Electronic)9781450393058
ISBN (Print)781665452120
DOIs
Publication statusPublished - May 2022
Event17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022 - Pittsburgh, United States
Duration: 18 May 202220 May 2022

Conference

Conference17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022
Country/TerritoryUnited States
CityPittsburgh
Period18/05/2220/05/22

Bibliographical note

Funding Information:
We thank the participants that contributed input to the study, the reviewers of the survey protocol, and Linnaeus University for hosting the survey. The financial support by Christian Doppler Research Association, the BMDW and the National Foundation for Research, Technology and Development is gratefully acknowledged.

Publisher Copyright:
© 2022 ACM.

Funding

We thank the participants that contributed input to the study, the reviewers of the survey protocol, and Linnaeus University for hosting the survey. The financial support by Christian Doppler Research Association, the BMDW and the National Foundation for Research, Technology and Development is gratefully acknowledged.

Keywords

  • difficulties applying self-Adaptation
  • feedback loops
  • industrial use cases
  • motivations
  • Self-Adaptation
  • survey

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