Verb-based Semantic Modelling and Analysis of Textual Requirements

Shubhashis Sengupta, Roshni Ramnani, Subhabrata Das, Anitha Chandran
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引用次数: 3

Abstract

Automated machine analysis of natural language requirements poses several challenges. Complex requirements such as functional requirements and use cases are hard to parse and analyze, the language itself is un-constrained, the flow of requirements may be haphazard, and one requirement may contradict another - to name a few challenges. In this paper, we present a lightweight semantic modeling technique through natural language processing to filter requirements and create a semi-formal semantic network of requirement sentences. We employ novel techniques of classification of verbs used in requirements, semantic role labeling, discourse identification, and a few verb entailment and dependency relationships to generate a lightweight semantic network and critique the requirements. We discuss the design of the model and some early results obtained from analyzing real-life industrial requirements.
基于动词的语义建模与语篇需求分析
自然语言需求的自动化机器分析提出了几个挑战。复杂的需求,如功能需求和用例,很难解析和分析,语言本身是不受约束的,需求流可能是偶然的,一个需求可能与另一个需求相矛盾——这只是一些挑战。在本文中,我们提出了一种轻量级的语义建模技术,通过自然语言处理来过滤需求并创建一个半形式化的需求句语义网络。我们采用新的技术,对需求中使用的动词进行分类,语义角色标记,话语识别,以及一些动词蕴涵和依赖关系,以生成轻量级语义网络并对需求进行批判。我们讨论了模型的设计和通过分析现实工业需求获得的一些早期结果。
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