A profiler for the matching process of henshin

A profiler for the matching process of henshin
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用于henshin匹配过程的分析器

DOI:
10.1145/3417990.3422000
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发表时间:
2020
期刊:
Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings
影响因子:
--
通讯作者:
Matthias Tichy
Matthias Tichy
中科院分区:
--
文献类型:
--
作者:
Raffaela Groner;Sophie Gylstorff;Matthias Tichy

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模型转换是模型驱动软件工程(MDSE)中的基本操作。由于在MDSE的帮助下开发的软件系统的规模和复杂性不断增加,转换的输入模型也越来越大。为了仍然能够有效地使用模型转换,应该更多地关注它们的性能。特别是对于声明性语言,转换的执行对开发人员来说是隐藏的,因此无法理解长时间执行的原因。我们展示了声明性转换语言Henshin的分析器,它提供了关于转换级别执行的信息。特别地,我们的分析器的目标是提供关于匹配过程的信息,以找到同构子图。在监视方法的帮助下,我们在运行时收集有关转换执行的信息,然后将其聚合并以各种可视化方式呈现给开发人员。在我们的工具演示中,我们展示了调用分析器的两种方法,并通过一个示例解释了分析器提供的信息。此外,我们将在示例的上下文中解释显示的信息,并展示如何实现可能的性能改进。该演示的屏幕截图可在https://youtu.be/TVq6MN8drJM上获得
Model transformations are essential operations in Model-Driven Software Engineering (MDSE). Due to the increasing size and complexity of software systems developed with the help of MDSE, the input models for transformations are also getting bigger. In order to still be able to use model transformations efficiently, more attention should be paid to their performance. Especially with declarative languages, the execution of a transformation remains hidden from the developer, so there is no way to understand the reasons for a long execution time.We present our profiler for the declarative transformation language Henshin, which provides information about the execution at the level of transformations. In particular, the goal of our profiler is to provide information about the matching process to find an isomorphic subgraph. With the help of our monitoring approach, we collect information about the transformation execution at runtime, which is then aggregated and presented to the developer in various visualizations.In our tool demo we present the two ways to invoke our profiler and explain by an example which information the profiler provides. In addition, we interpret the displayed information in the context of our example and show how a possible performance improvement can be achieved. A screencast of the demo is available at https://youtu.be/TVq6MN8drJM
DOI: --
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