Automated Variability Injection for Graphical Modelling Languages

  • Antonio Garmendia (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

Model-based development approaches, such as Model-Driven Engineering (MDE), heavily rely on the use of modelling languages to achieve and automate software development tasks. To enable the definition of model variants (e.g., supporting the compact description of system families), one solution is to combine MDE with Software Product Lines. However, this is technically costly as it requires adapting many MDE artefacts associated to the modelling language – especially the meta-models and graphical environments. To alleviate this situation, we propose a method for the automated injection of variability into graphical modelling languages. Given the meta-model and graphical environment of a particular language, our approach permits configuring the allowed model variability, and the graphical environment is automatically adapted to enable creating models with variability. Our solution is implemented atop the Eclipse Modeling Framework and Sirius, and synthesizes adapted graphical editors integrated with Feature IDE.
Period15 Nov 2020
Event title9th ACM SIGPLAN International Conference on Generative Programming, Concepts and Experiences (GPCE 2020), November 16–17, 2020, Chicago, USA, Virtual
Event typeConference
LocationAustriaShow on map

Fields of science

  • 202017 Embedded systems
  • 102006 Computer supported cooperative work (CSCW)
  • 201132 Computational engineering
  • 502032 Quality management
  • 503015 Subject didactics of technical sciences
  • 502050 Business informatics
  • 207409 Navigation systems
  • 102020 Medical informatics
  • 102022 Software development
  • 102002 Augmented reality
  • 201305 Traffic engineering
  • 102034 Cyber-physical systems
  • 102015 Information systems
  • 102040 Quantum computing 
  • 509026 Digitalisation research
  • 211928 Systems engineering
  • 102027 Web engineering
  • 102016 IT security

JKU Focus areas

  • Digital Transformation