From natural language requirements to UML class diagrams

Richa Sharma, P. K. Srivastava, K. K. Biswas
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引用次数: 18

Abstract

Unified Modeling Language (UML) is the most popular modeling language for analysis, design and development of the software system. There has been a lot of research interest in generating these UML models, especially class diagrams, automatically from Natural Language requirements. The interest in class diagrams can be attributed to the fact that classes represent the abstractions present in the system to be developed. However, automated generation of UML class diagrams is a challenging task as it involves lot of pre-processing or manual intervention at times. In this paper, we present dependency analysis based approach to derive UML class diagrams automatically from Natural Language requirements. We transform the requirements statements to an intermediary frame-based structured representation using dependency analysis of requirements statements and the Grammatical Knowledge Patterns. The knowledge stored in the frame-based structured representation is used to derive class diagrams using rule-based algorithm. Our approach has generated similar class diagrams as reported in earlier works based on linguistic analysis with either annotation or manual intervention. We present the effectiveness of our approach in terms of recall and precision for the case-studies presented in earlier works.
从自然语言需求到UML类图
统一建模语言(UML)是用于软件系统分析、设计和开发的最流行的建模语言。有很多研究兴趣在自动地从自然语言需求生成这些UML模型,特别是类图。对类图的兴趣可以归因于这样一个事实,即类表示要开发的系统中存在的抽象。然而,UML类图的自动生成是一项具有挑战性的任务,因为它有时涉及大量的预处理或人工干预。在本文中,我们提出了基于依赖分析的方法,从自然语言需求中自动派生UML类图。我们使用需求陈述的依赖性分析和语法知识模式将需求陈述转换为中间的基于框架的结构化表示。将存储在基于框架的结构化表示中的知识用于使用基于规则的算法派生类图。我们的方法已经生成了类似的类图,正如在早期的作品中报告的那样,这些类图是基于带有注释或人工干预的语言分析。我们在早期作品中提出的案例研究的召回率和准确性方面提出了我们的方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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