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An Exploratory Experiment on Metamodel-Transformation Co-Evolution

机译:元模型-变换协同进化的探索性实验

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Metamodels, like any other software artifacts evolve throughout time. As a consequence, all dependent artifacts may need to be co-evolved accordingly, including model transformations. Transformations are a key component of an automated development solution, thus it is crucial to automate their co-evolution while guaranteeing that they remain correct. However, there is little known about what aspects and characteristics must be automated in a manual co-evolution and in particular how it should be correctly automated. Few approaches exist, but it is not clear to what extent those approaches are able to automate the manual co-evolution of model transformations. In this paper, we report on an exploratory experiment we conducted to better understand the co-evolution of transformations in practice and to assess the usefulness of the current existing techniques. 15 participants were involved in our experiment to monitor how they co-evolve transformation rules in response to metamodel evolution. Our analysis results show that while existing approaches support the user with an automatic impact analysis, they do not consider proposing a very large spectrum of alternative resolutions. Among the 14 resolutions that occurred in our experiment, on average only 4 (up to 6) were supported by the existing approaches.
机译:像任何其他软件工件一样,元模型会随时间演变。结果,所有依赖的工件可能需要相应地共同演化,包括模型转换。转换是自动化开发解决方案的关键组成部分,因此,在保证其正确性的同时,自动化其协同进化至关重要。但是,对于手动协同进化中哪些方面和特征必须自动进行,尤其是如何正确地进行自动化,鲜为人知。很少有方法,但是尚不清楚这些方法在多大程度上能够使模型转换的手动协同进化自动化。在本文中,我们报告了进行的探索性实验,以更好地理解实践中转换的共同进化并评估现有技术的实用性。 15名参与者参与了我们的实验,以监测他们如何共同响应元模型的演化而演变规则。我们的分析结果表明,尽管现有方法通过自动影响分析为用户提供支持,但他们并未考虑提出非常广泛的替代解决方案。在我们的实验中发生的14种分辨率中,现有方法平均仅支持4种(最多6种)。

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