Supporting a Model-driven Development Process for Distributed Control Software

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Abstract

Established development processes for industrial control systems are static and struggle to adopt changing requirements. The interdisciplinary nature of such systems necessitates carefully designed interfaces between modules and components, as well as unambiguously defined requirements. The domain-specific modeling language IEC 61499 offers potentials to accelerate design processes and to introduce a model-driven approach, in which interface and behavior models are continuously refined and reused. We investigate these potentials and outline how to apply an extended development process in which implicit expert knowledge is preserved in behavior- and interface models that are currently not retained during the development. Based on a running example, we illustrate the refinement of scenarios along the development process and show how the retained information captures the expected behavior of the environment. We identify research questions and gaps in the elicitation, maintenance and utilization of these models, in particular in the domains of model-based testing, monitoring, and reconfiguration. An accelerated development process that integrates behavior models can help making future industrial control systems more dependable, flexible, and resilient during the whole life cycle.
Original languageEnglish
Title of host publication2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation, ETFA 2022
Place of PublicationNew York City, USA
PublisherIEEE
Pages1-8
Number of pages8
ISBN (Electronic)9781665499965
ISBN (Print)978-1-6654-9996-5, 978-1-6654-9996-5
DOIs
Publication statusPublished - Oct 2022

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2022-September
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Fields of science

  • 202017 Embedded systems
  • 102022 Software development
  • 102025 Distributed systems
  • 102029 Practical computer science
  • 202003 Automation
  • 202041 Computer engineering
  • 102 Computer Sciences

JKU Focus areas

  • Digital Transformation

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