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Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation

Published: 28 September 2022 Publication History

Abstract

Artifacts support evaluating new research results and help comparing them with the state of the art in a field of interest. Over the past years, several artifacts have been introduced to support research in the field of self-adaptive systems. While these artifacts have shown their value, it is not clear to what extent these artifacts support research on problems in self-adaptation that are relevant to industry. This paper provides a set of guidelines for artifacts that aim at supporting industry-relevant research on selfadaptation. The guidelines that are grounded on data obtained from a survey with practitioners were derived during working sessions at the 17th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. Artifact providers can use the guidelines for aligning future artifacts with industry needs; they can also be used to evaluate the industrial relevance of existing artifacts. We also propose an artifact template.

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Cited By

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  • (2024)Generative AI for Self-Adaptive Systems: State of the Art and Research RoadmapACM Transactions on Autonomous and Adaptive Systems10.1145/368680319:3(1-60)Online publication date: 30-Sep-2024
  • (2023)Self-Adaptation in Industry: A SurveyACM Transactions on Autonomous and Adaptive Systems10.1145/358922718:2(1-44)Online publication date: 28-May-2023
  • (2023)CHESS: A Framework for Evaluation of Self-Adaptive Systems Based on Chaos Engineering2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)10.1109/SEAMS59076.2023.00033(195-201)Online publication date: May-2023
  • Show More Cited By

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Information & Contributors

Information

Published In

cover image ACM SIGSOFT Software Engineering Notes
ACM SIGSOFT Software Engineering Notes  Volume 47, Issue 4
October 2022
31 pages
ISSN:0163-5948
DOI:10.1145/3561846
Issue’s Table of Contents
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2022
Published in SIGSOFT Volume 47, Issue 4

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Cited By

View all
  • (2024)Generative AI for Self-Adaptive Systems: State of the Art and Research RoadmapACM Transactions on Autonomous and Adaptive Systems10.1145/368680319:3(1-60)Online publication date: 30-Sep-2024
  • (2023)Self-Adaptation in Industry: A SurveyACM Transactions on Autonomous and Adaptive Systems10.1145/358922718:2(1-44)Online publication date: 28-May-2023
  • (2023)CHESS: A Framework for Evaluation of Self-Adaptive Systems Based on Chaos Engineering2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)10.1109/SEAMS59076.2023.00033(195-201)Online publication date: May-2023
  • (2023)On the Need for Artifacts to Support Research on Self-Adaptation Mature for Industrial Adoption2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)10.1109/SEAMS59076.2023.00020(86-87)Online publication date: May-2023

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