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Automated Reuse of Model Transformations through Typing Requirements Models.
- Source :
- ACM Transactions on Software Engineering & Methodology; Sep2019, Vol. 28 Issue 4, p1-62, 62p
- Publication Year :
- 2019
-
Abstract
- Model transformations are key elements of model-driven engineering, where they are used to automate the manipulation of models. However, they are typed with respect to concrete source and target meta-models, making their reuse for other (even similar) meta-models challenging. To improve this situation, we propose capturing the typing requirements for reusing a transformation with other meta-models by the notion of a typing requirements model (TRM). A TRM describes the prerequisites that amodel transformation imposes on the source and targetmeta-models to obtain a correct typing. The key observation is that any meta-model pair that satisfies the TRM is a valid reuse context for the transformation at hand. A TRM is made of two domain requirement models (DRMs) describing the requirements for the source and target meta-models, and a compatibility model expressing dependencies between them. We define a notion of refinement between DRMs and see meta-models as a special case of DRM. We provide a catalogue of valid refinements and describe how to automatically extract a TRM from an ATL transformation. The approach is supported by our tool TOTEM. We report on two experiments--based on transformations developed by third parties and meta-model mutation techniques--validating the correctness and completeness of our TRM extraction procedure and confirming the power of TRMs to encode variability and support flexible reuse. [ABSTRACT FROM AUTHOR]
- Subjects :
- EXTRACTION techniques
REQUIREMENTS engineering
TECHNICAL specifications
Subjects
Details
- Language :
- English
- ISSN :
- 1049331X
- Volume :
- 28
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- ACM Transactions on Software Engineering & Methodology
- Publication Type :
- Academic Journal
- Accession number :
- 138565057
- Full Text :
- https://doi.org/10.1145/3340108