TiQi: Towards natural language trace queries

Piotr Pruski, Sugandha Lohar, Rundale Aquanette, Greg Ott, Sorawit Amornborvornwong, A. Rasin, J. Cleland-Huang
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引用次数: 10

Abstract

One of the surprising observations of traceability in practice is the under-utilization of existing trace links. Organizations often create links in order to meet compliance requirements, but then fail to capitalize on the potential benefits of those links to provide support for activities such as impact analysis, test regression selection, and coverage analysis. One of the major adoption barriers is caused by the lack of accessibility to the underlying trace data and the lack of skills many project stakeholders have for formulating complex trace queries. To address these challenges we introduce TiQi, a natural language approach, which allows users to write or speak trace queries in their own words. TiQi includes a vocabulary and associated grammar learned from analyzing NL queries collected from trace practitioners. It is evaluated against trace queries gathered from trace practitioners for two different project environments.
TiQi:走向自然语言跟踪查询
在实践中,对可追溯性的一个令人惊讶的观察是对现有跟踪链接的利用不足。组织经常为了满足遵从性需求而创建链接,但是随后未能利用这些链接的潜在好处来为诸如影响分析、测试回归选择和覆盖率分析等活动提供支持。主要的采用障碍之一是由于缺乏对底层跟踪数据的可访问性,以及许多项目涉众缺乏制定复杂跟踪查询的技能。为了应对这些挑战,我们引入了TiQi,这是一种自然语言方法,允许用户用自己的话编写或说出跟踪查询。TiQi包括通过分析从跟踪实践者那里收集的NL查询学到的词汇表和相关语法。它是根据从两个不同项目环境的跟踪执行者收集的跟踪查询进行评估的。
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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