Abstract
The use of Model Driven Development (MDD) approach is increasing in industry. MDD approach raises the level of abstraction using models as main artifacts of software engineering processes. The development of model transformations is a critical step in MDD. Tasks for defining, specifying and maintaining model transformation rules can be complex in MDD. Model Transformation By Example (MTBE) approaches have been proposed to ease the development process of transformation rules. Starting from pairs of example models the transformation rules are derived semi-automatically.
The aim of our approach is to derive the adaptation operations that must be implemented in a legacy model transformation to fulfill a new transformation requirement. An MTBE approach and a tool to develop and evolve ATL transformation rules have been developed. Our approach derives the transformations operations automatically using execution traceability data and models differences. The developed MTBE approach can be applied to evolve legacy model transformations. The tool can be used with endogenous and exogenous model to model transformations. The approach has been validated with several model transformations and the results have been collected. A real case study is introduced to demonstrate the usefulness of the tool.
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Acknowledgements
This work has been developed in the DA2SEC project and UE2014-12 AURE project context funded by the Department of Education, Universities and Research of the Basque Government. The work has been developed by the embedded system group supported by the Department of Education, Universities and Research of the Basque Government.
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Agirre, J.A., Sagardui, G., Etxeberria, L. (2015). Model Transformation by Example Driven ATL Transformation Rules Development Using Model Differences. In: Holzinger, A., Cardoso, J., Cordeiro, J., Libourel, T., Maciaszek, L., van Sinderen, M. (eds) Software Technologies. ICSOFT 2014. Communications in Computer and Information Science, vol 555. Springer, Cham. https://doi.org/10.1007/978-3-319-25579-8_7
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