Custom-Developed vs. Model-based Configuration Tools: Experiences from an Industrial Automation Ecosystem

Daniela Lettner, Michael Petruzelka, Rick Rabiser, Florian Angerer, Herbert Prähofer, Paul Grünbacher

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

Abstract

High demands regarding the variability of automation software motivate organizations to automate the configuration process. In practice, this often leads to the development of custom configuration tools designed specifically for configuring the automation software they were developed for. This approach works well as long as both, the development of the software and the configurator are under the full control of the organization. However, software platforms are increasingly open, i.e., key customers add capabilities and thereby change the platform's variability. Often, these customers create a new platform themselves, which they offer to their customers. Moving from a closed platform to a software ecosystem means that development and variability management happen at multiple layers involving multiple teams with different backgrounds. This poses new requirements regarding the flexibility of configuration tools. In this paper, we report experiences and issues with a custom-developed configurator currently in use in an industrial automation software ecosystem. We describe how a model-based tool can be applied to address these issues and provide a scenario-based comparison of the custom-developed solution and the model-based configurator.
Original languageEnglish
Title of host publicationProceedings MAPLE/SCALE 2013 Workshop at the 17th International Software Product Line Conference
Place of PublicationNew York, NY, USA
PublisherACM
Pages52-58
Number of pages7
ISBN (Print)978-1-4503-2325-3
DOIs
Publication statusPublished - 2013

Fields of science

  • 102 Computer Sciences
  • 102009 Computer simulation
  • 102011 Formal languages
  • 102013 Human-computer interaction
  • 102029 Practical computer science
  • 102022 Software development
  • 102024 Usability research

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)

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