从NL到SBVR的模型转换

Shabana Ramzan, Imran Sarwar Bajwa, I. Haq, M. Naeem
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引用次数: 10

摘要

在需求工程中,需求通常是用自然语言的句子来写的,而自然语言是模糊和不一致的,所以用自然语言写的需求也往往是模糊的。为了避免这种歧义问题,我们提出了一种基于SBVR(业务词汇和业务规则语义)的模型转换方法来生成需求。源元模型(NL)中提供的信息自动转换为目标元模型(SBVR)。SBVR元模型不仅可以被机器加工,而且为软件设计提供了精确可靠的模型。标准的SBVR元模型已经可用,但是对于自然语言,我们提出了我们自己的元模型,因为没有用于自然语言的标准元模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A model transformation from NL to SBVR
In Requirement Engineering, requirements are usually written in sentences of natural language and natural languages are ambiguous and inconsistent, so the requirements written in natural languages also tend to be ambiguous. To avoid this problem of ambiguity we present an approach of model transformation to generate requirements based on SBVR (Semantics of Business Vocabulary and Business Rules). The information provided in source metamodel (NL) is automatically transformed into target metamodel (SBVR). SBVR metamodel can not only be processed by machine but also provides precise and reliable model for software design. The standard SBVR metamodel is already available but for natural language we proposed our own metamodel because there is no standard metamodel available for natural languages.
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