Detecting Vague Words & Phrases in Requirements Documents in a Multilingual Environment

Breno Dantas Cruz, Bargav Jayaraman, Anurag Dwarakanath, Collin McMillan
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引用次数: 10

Abstract

Vagueness in software requirements documents can lead to several maintenance problems, especially when the customer and development team do not share the same language. Currently, companies rely on human translators to maintain communication and limit vagueness by translating the requirement documents by hand. In this paper, we describe two approaches that automatically identify vagueness in requirements documents in a multilingual environment. We perform two studies for calibration purposes under strict industrial limitations, and describe the tool that we ultimately deploy. In the first study, six participants, two native Portuguese speakers and four native Spanish speakers, evaluated both approaches. Then, we conducted a field study to test the performance of the best approach in real-world environments at two companies. We describe several lessons learned for research and industrial deployment.
多语言环境下需求文档中模糊词和短语的检测
软件需求文档中的模糊性可能导致一些维护问题,特别是当客户和开发团队不使用相同的语言时。目前,公司依靠人工翻译来保持沟通,并通过手工翻译需求文档来限制模糊性。在本文中,我们描述了在多语言环境中自动识别需求文档中的模糊性的两种方法。我们在严格的工业限制下进行了两项研究,用于校准目的,并描述了我们最终部署的工具。在第一项研究中,六名参与者,两名母语为葡萄牙语的人和四名母语为西班牙语的人,对两种方法进行了评估。然后,我们在两家公司进行了实地研究,以测试最佳方法在现实环境中的性能。我们描述了研究和工业部署的几个经验教训。
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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