解决需求规范中的不确定性,生成UML图

Gaurav A. Patel, A. Priya
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引用次数: 3

摘要

模糊是软件需求说明中的一个关键问题。需求通常用自然语言表示。然而,自然语言中的表达式可能存在歧义。因此,当需求被分析时,歧义在可能的范围内被解决是必要的,这样软件规范就不会有任何潜在的误解。解决歧义的一个有吸引力的替代方案是将非正式的自然语言需求转换为其正式或半正式的对应需求,以确保精度和正交性。为了达到这个目标,可以利用统一建模语言的符号。由于本质上是图形化的,UML符号可以很容易地被用户理解,同时,由于由正交的语法/语义约定驱动,这些符号有助于极大地减少歧义。建议的工作旨在支持基于文本的信息作为需求规范。它解决了不确定性,找到了UML组件及其之间的关系,生成了准确的UML图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resolve the uncertainity in requirement specification to generate the UML diagram
Ambiguity is a critical problem in the software requirement specifications. Requirements are typically expressed in a natural language. However, expressions in natural languages are likely to suffer from ambiguities. Hence, it is essential that when the requirements are analyzed, the ambiguities are resolved to the extent possible, so that the software specifications are free of any potential misinterpretations. One of the attractive alternatives in resolving ambiguities is to convert the informal natural language requirements into their formal or semi-formal counterpart that ensures precision and orthogonality. Towards meeting this goal, the Unified Modeling Language notations can be exploited to an advantage. Being graphical in nature, the UML notations can be easily comprehended by the user and at the same time, being driven by orthogonal syntactic/semantic conventions, the notations help reduce ambiguities greatly. The proposed work is aimed to support the text based information as the requirement specification. It resolves the uncertainty and find the UML components and the relationship among them to generate the accurate the UML Diagram.
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