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Automatic Transformation Co-evolution Using Traceability Models and Graph Transformation

机译:使用可追溯性模型和图变换的自动变换协同进化

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In rule-based approaches, a model transformation definition tells how an instance of a source model should be transformed to an instance of a target model. As these models undergo changes, model transformations defined over these models may get out of sync. Restoring conformance between model transformations and the models is a complex and error prone task. In this paper, we propose a formal approach to automatically co-evolve model transformations according to the evolution of the models. The approach is based on encoding the model transformation definition as a traceability model and the evolution of the models as applications of graph transformation rules. These rules are used to obtain an evolved traceability model from the original trace-ability model. We will identify the criteria which need to be fulfilled in order to make this automatic co-evolution possible. We provide a tool support for this procedure, in which the evolved model transformation definition is derived from the evolved traceability model.
机译:在基于规则的方法中,模型转换定义告诉如何将源模型的实例转换为目标模型的实例。随着这些模型的变化,在这些模型上定义的模型转换可能会不同步。恢复模型转换与模型之间的一致性是一项复杂且容易出错的任务。在本文中,我们提出了一种根据模型的演化自动共同演化模型变换的正式方法。该方法基于将模型转换定义编码为可追溯性模型,并将模型的演变编码为图转换规则的应用。这些规则用于从原始可跟踪性模型中获取经过改进的可跟踪性模型。我们将确定使自动协同进化成为可能所需满足的标准。我们为此过程提供了工具支持,其中演化模型转换定义是从演化可追溯性模型派生的。

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