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Automatically Discovering Hidden Transformation Chaining Constraints

机译:自动发现隐藏的转换链约束

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Model transformations operate on models conforming to precisely defined metamodels. Consequently, it often seems relatively easy to chain them: the output of a transformation may be given as input to a second one if metamodels match. However, this simple rule has some obvious limitations. For instance, a transformation may only use a subset of a metamodel. Therefore, chaining transformations appropriately requires more information.rnWe present here an approach that automatically discovers more detailed information about actual chaining constraints by statically analyzing transformations. The objective is to provide developers who decide to chain transformations with more data on which to base their choices. This approach has been successfully applied to the case of a library of endogenous transformations. They all have the same source and target metamodel but have some hidden chaining constraints. In such a case, the simple metamodel matching rule given above does not provide any useful information.
机译:模型转换对符合精确定义的元模型的模型进行操作。因此,将它们链接起来似乎通常比较容易:如果元模型匹配,则可以将转换的输出作为第二个输入的输入。但是,此简单规则有一些明显的局限性。例如,转换只能使用元模型的子集。因此,链接转换适当地需要更多信息。在此,我们提出一种方法,该方法通过静态分析转换来自动发现有关实际链接约束的更详细信息。目的是为决定链接转换的开发人员提供更多数据,以作为他们选择的基础。这种方法已经成功地应用于内源转化文库的情况。它们都具有相同的源和目标元模型,但是具有一些隐藏的链接约束。在这种情况下,上面给出的简单元模型匹配规则不会提供任何有用的信息。

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