On using Inplace Transformations for Model Co-evolution

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Abstract

Metamodel evolution and model co-evolution are considered to be essential ingredients for the successful adoption of model-driven engineering in practice. In this respect, on the one hand, dedicated co- evolution languages have been proposed for migrating models conforming to an initial metamodel to models conforming to a revised metamodel with the drawback of requiring to learn a new language. On the other hand, the employment of dedicated model-to-model transformation languages has been proposed demanding for the specification of rules for copying unchanged elements. In this paper, we propose to tackle the co-evolution problem from a different viewpoint. Instead of describing the co-evolution of models as a transformation between two metamodels, we employ existing inplace transformation languages. For this, the prerequisite is to represent both language versions within one metamodel which is automatically computed by merging the initial and the revised metamodel. This ensures that the initial as well as the revised model conform to the merged metamodel, enabling the employment of inplace transformations for initializing new metamodel elements. Finally, a check-out transformation is used for eliminating model elements which are no longer covered by the revised metamodel.We demonstrate this idea by using ATL for merging the metamodels and realizing the check-out transformation. Furthermore, we discuss the ATL refinement mode for co-evolving the models.
Original languageEnglish
Title of host publicationProceedings of 2nd International Workshop on Model Transformation with ATL
Number of pages14
Publication statusPublished - 2010

Fields of science

  • 101004 Biomathematics
  • 101027 Dynamical systems
  • 101028 Mathematical modelling
  • 101029 Mathematical statistics
  • 101014 Numerical mathematics
  • 101015 Operations research
  • 101016 Optimisation
  • 101017 Game theory
  • 101018 Statistics
  • 101019 Stochastics
  • 101024 Probability theory
  • 101026 Time series analysis
  • 102 Computer Sciences
  • 102001 Artificial intelligence
  • 102003 Image processing
  • 102004 Bioinformatics
  • 102013 Human-computer interaction
  • 102018 Artificial neural networks
  • 102019 Machine learning
  • 103029 Statistical physics
  • 106005 Bioinformatics
  • 106007 Biostatistics
  • 202017 Embedded systems
  • 202035 Robotics
  • 202036 Sensor systems
  • 202037 Signal processing
  • 305901 Computer-aided diagnosis and therapy
  • 305905 Medical informatics
  • 305907 Medical statistics
  • 102032 Computational intelligence
  • 102033 Data mining
  • 101031 Approximation theory
  • 102002 Augmented reality
  • 102006 Computer supported cooperative work (CSCW)
  • 102015 Information systems
  • 102021 Pervasive computing
  • 102025 Distributed systems
  • 102027 Web engineering
  • 202038 Telecommunications

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