文章基本信息

标题：Incremental Model Transformation with Epsilon in Model-Driven Engineering
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作者：Marzieh Ghorbani ; Mohammadreza Sharbaf ; Bahman Zamani 等
期刊名称：Acta Informatica Pragensia
电子版ISSN：1805-4951
出版年度：2022
卷号：11
期号：2
页码：179-204
DOI：10.18267/j.aip.179
语种：Czech
出版社：University of Economics, Prague
摘要：Model-Driven Engineering (MDE) is a software development paradigm that uses models as the main artifacts in the development process. MDE uses model transformations to propagate changes between source and target models. In some development scenarios, target models should be updated based on the evolution of source models. In such cases, it is required to re-execute all transformation rules to update the target model. Incremental execution of transformations, which partially executes the transformation rules, is a solution to this problem. The Epsilon Transformation Language (ETL) is a well-known model transformation language that does not support incremental executions. In this paper, we propose an approach to support the incremental execution of ETL transformations. Our proposal includes a process, as well as a prototype, to propagate changes to the target model. In the proposed approach, all the changes in the source model are detected to identify and re-execute the rules which deal with computing the required elements for updating the target model. We evaluated the correctness and performance of our approach by means of a case study. Compared to the standard ETL, the results are promising regarding the correctness of target models as well as faster execution of the transformation.