Abstract
AbstractIn the Model-Driven Architecture (MDA)
paradigm the Query/View/Transformation (QVT) standard
plays a vital role for model transformations. Especially the
high-level declarative QVT Relations language, however, has
not yet gained widespread use in practice. This is not least due
to missing tool support in general and inadequate debugging
support in particular. Transformation engines interpreting
QVT Relations operate on a low level of abstraction, hide
the operational semantics of a transformation and scatter
metamodels, models, QVT code, and trace information across
different artifacts.
We therefore propose a model-based debugger representing
QVT Relations on bases of TROPIC, a model transformation
language utilizing a variant of Colored Petri Nets (CPNs). As
a prerequisite for convenient debugging, TROPIC provides a
homogeneous view on all artifacts of a transformation on basis
of a single formalism. Besides that, this formalism also provides
a runtime model, thus making the afore hidden operational
semantics of the transformation explicit. Using an explicit
runtime model allows to employ model-based techniques for
debugging, e.g., using the Object Constraint Language (OCL)
for simply defining breakpoints and querying the execution
state of a transformation.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 24th International Conference on Automated Software Engineering (ASE 2009), IEEE, pp. 1-12, 2009 |
| Number of pages | 12 |
| Publication status | Published - 2009 |
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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