朝着从自然语言规范中自动提取UML类图的方向发展

Song Yang, H. Sahraoui
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引用次数: 3

摘要

在模型驱动工程(MDE)中,UML类图作为开发人员之间进行计划和通信的一种方式。然而,它是复杂和消耗资源的。我们提出了一种从自然语言软件规范中提取UML类图的自动化方法。为了开发我们的方法,我们在志愿者的帮助下创建了UML类图和它们的英文规范的数据集。我们的方法是一个步骤的管道,包括将输入分割成句子,对句子进行分类,从句子中生成UML类图片段,以及将这些片段组合成一个UML类图。我们开发了一个特定于UML类图提取的定量测试框架。我们的方法精度和召回率较低,但可以作为未来研究的基准。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards automatically extracting UML class diagrams from natural language specifications
In model-driven engineering (MDE), UML class diagrams serve as a way to plan and communicate between developers. However, it is complex and resource-consuming. We propose an automated approach for the extraction of UML class diagrams from natural language software specifications. To develop our approach, we create a dataset of UML class diagrams and their English specifications with the help of volunteers. Our approach is a pipeline of steps consisting of the segmentation of the input into sentences, the classification of the sentences, the generation of UML class diagram fragments from sentences, and the composition of these fragments into one UML class diagram. We develop a quantitative testing framework specific to UML class diagram extraction. Our approach yields low precision and recall but serves as a benchmark for future research.
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