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Catch Me If You Can - Debugging Support for Model Transformations

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

Abstract

Model-Driven Engineering places models as first-class artifacts throughout the software lifecycle requiring the availability of proper transformation languages. Although numerous approaches are available, they lack convenient facilities for supporting debugging and understanding of the transformation logic. This is because execution engines operate on a low level of abstraction, hide the operational semantics of a transformation, scatter metamodels, models, transformation logic, and trace information across different artifacts, and provide limited verification support. To tackle these problems, we propose a Domain-Specific Language (DSL) on top of Colored Petri Nets (CPNs) - called Transformation Nets - for the execution and debugging of model transformations on a high level of abstraction. This formalism makes the afore hidden operational semantics explicit by providing a runtime model in terms of places, transitions and tokens, integrating all artifacts involved into a homogenous view. Moreover, the formal underpinnings of CPNs enable comprehensive verification of model transformations.
Original languageEnglish
Title of host publicationModels in Software Engineering Workshops and Symposia at MODELS 2009, Denver, CO, USA, October 4-9
Pages5-20
Number of pages16
DOIs
Publication statusPublished - 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6002 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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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