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Using default reasoning to discover inconsistencies in natural language requirements

机译:使用默认推理发现自然语言要求中的不一致之处

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The use of logic in identifying and analysing inconsistency in requirements from multiple stakeholders has been found to be effective in a number of studies. Default reasoning is a theoretically well founded formalism that is especially suited for supporting the evolution of requirements. However, direct use of logic in eliciting requirements and in discussing them with stakeholders poses serious useability problems. In this paper we explore the integration of natural language parsing techniques with default reasoning to overcome these difficulties. We also propose a method for automatically discovering scenarios that expose inconsistencies in requirements, and show how to deal with them in a formal manner. These techniques were implemented and tested in a prototype tool called CARL.
机译:在许多研究中发现,在识别和分析多个利益相关者的需求不一致方面使用逻辑是有效的。默认推理是一种理论上有据可查的形式主义,特别适合于支持需求的演变。但是,在引出需求并与利益相关者讨论需求时直接使用逻辑会带来严重的可用性问题。在本文中,我们探索了自然语言解析技术与默认推理的集成,以克服这些困难。我们还提出了一种方法,用于自动发现暴露需求不一致的场景,并显示如何以正式方式处理它们。这些技术是在称为CARL的原型工具中实施和测试的。

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