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SEAByTE: A Self-Adaptive Micro-service System Artifact for Automating A/B Testing
Katholieke Universiteit Leuven, Belgium.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Katholieke Universiteit Leuven, Belgium. (DISA;DISA-SIG;Adaptwise)ORCID iD: 0000-0002-1162-0817
2022 (English)In: Proceedings - 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022, ACM Press, 2022, p. 77-83Conference paper, Published paper (Refereed)
Abstract [en]

Micro-services are a common architectural approach to software development today. An indispensable tool for evolving micro-service systems is A/B testing. In A/B testing, two variants, A and B, are applied in an experimental setting. By measuring the outcome of an evaluation criterion, developers can make evidence-based decisions to guide the evolution of their software. Recent studies highlight the need for enhancing the automation when such experiments are conducted in iterations. To that end, we contribute a novel artifact that aims at enhancing the automation of an experimentation pipeline of a micro-service system relying on the principles of self-Adaptation. Concretely, we propose SEAByTE, an experimental framework for testing novel self-Adaptation solutions to enhance the automation of continuous A/B testing of a micro-service based system. We illustrate the use of the SEAByTE artifact with a concrete example.

Place, publisher, year, edition, pages
ACM Press, 2022. p. 77-83
Keywords [en]
Software design, A/B testing; Architectural approach; Continuous deployment; Evaluation criteria; Evidence- based decisions; Indispensable tools; Micro services; Self- adaptations; Service systems; Service-based systems, Automation
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-118134DOI: 10.1145/3524844.3528081Scopus ID: 2-s2.0-85134157644ISBN: 9781450393058 (print)OAI: oai:DiVA.org:lnu-118134DiVA, id: diva2:1723792
Conference
17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022, Pittsburgh 18-20 May 2022
Available from: 2023-01-04 Created: 2023-01-04 Last updated: 2023-05-11Bibliographically approved

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Weyns, Danny

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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