Environment-Driven Abstraction Identification for Requirements-Based Testing

Zedong Peng, Prachi Rathod, Nan Niu, Tanmay Bhowmik, Hui Liu, Lin Shi, Zhi Jin
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引用次数: 10

Abstract

Abstractions are significant domain terms that have assisted in requirements elicitation and modeling. To extend the assistance towards requirements validation, we present in this paper an automated approach to identifying the abstractions for supporting requirements-based testing. We select relevant Wikipedia pages to serve as a domain corpus that is independent from any specific software system. We further define five novel patterns based on part-of-speech tagging and dependency parsing, and frame our candidate abstractions in the form of pairs for better testability. We evaluate our approach with six software systems in two application domains: Electronic health records and Web conferencing. The results show that our abstractions are more accurate than those generated by two of the state-of-the-art techniques. Initial findings also indicate our abstractions’ capabilities of revealing bugs and matching the environmental assumptions created manually.
基于需求测试的环境驱动抽象识别
抽象是重要的领域术语,有助于需求的引出和建模。为了扩展对需求验证的帮助,我们在本文中提出了一种自动化的方法来识别支持基于需求的测试的抽象。我们选择相关的维基百科页面作为独立于任何特定软件系统的领域语料库。我们进一步定义了基于词性标记和依赖解析的五种新模式,并以对的形式构建候选抽象,以获得更好的可测试性。我们用两个应用领域的六个软件系统来评估我们的方法:电子健康记录和网络会议。结果表明,我们的抽象比两种最先进的技术生成的抽象更准确。最初的发现还表明,我们的抽象具有揭示错误和匹配手动创建的环境假设的能力。
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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