TiQi: Towards natural language trace queries
TiQi: Towards natural language trace queries
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TiQi：走向自然语言跟踪查询
DOI：
10.1109/re.2014.6912254
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
J. Cleland
中科院分区：
文献类型：
--
作者：
Piotr Pruski;Sugandha Lohar;Rundale Aquanette;Greg Ott;Sorawit Amornborvornwong;A. Rasin;J. Cleland
实践中可追溯性的令人惊讶的观察之一是现有痕量链接的利用不足。组织通常会创建链接以满足合规要求，但随后无法利用这些链接的潜在好处，以提供对诸如影响分析，测试回归选择和覆盖范围分析等活动的支持。主要的采用障碍之一是由于缺乏对基本痕量数据的可访问性以及许多项目利益相关者对复杂痕量查询所具有的技能的缺乏。为了应对这些挑战，我们介绍了一种自然语言方法TIQI，该方法允许用户用自己的文字编写或说出跟踪查询。 TIQI包括从分析从微量从业者那里收集的NL查询中学到的词汇和相关语法。它是根据从从业人员那里收集的两个不同项目环境的跟踪查询进行评估的。
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.
安全关键项目的战略可追溯性
影响因子：
3.3
作者：
Mäder;Patrick;Cleland-Huang Jane
通讯作者：
Cleland-Huang Jane