审查自动生成的跟踪链接:哪些信息对人类分析人员有用?

Salome Maro, Jan-Philipp Steghöfer, J. Hayes, J. Cleland-Huang, M. Staron
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引用次数: 11

摘要

自动化可追溯性已经研究了十多年,并取得了可喜的成果。然而,需要人工分析人员来审查生成的跟踪链接,以确保其质量。审查跟踪链接的过程不是微不足道的,虽然以前的研究已经分析了人类分析师的表现,但它们并没有关注分析师的信息需求。本研究的目的是调查人类分析师需要什么样的上下文信息。我们使用了设计科学研究,在该研究中,我们与可追溯性领域的十位实践者进行了访谈,以了解人类分析师所需的信息。然后,我们将从访谈中收集的信息与现有文献进行比较。我们创建了一个原型工具,将这些信息呈现给人类分析师。为了进一步了解上下文信息的作用,我们对33名参与者进行了对照实验。我们的访谈显示,人类分析师需要来自三个不同来源的信息:1)通过链接连接的工件,2)来自可追溯性信息模型,以及3)来自跟踪算法。实验结果表明,连接工件的内容比工件的上下文信息对分析人员更有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vetting Automatically Generated Trace Links: What Information is Useful to Human Analysts?
Automated traceability has been investigated for over a decade with promising results. However, a human analyst is needed to vet the generated trace links to ensure their quality. The process of vetting trace links is not trivial and while previous studies have analyzed the performance of the human analyst, they have not focused on the analyst's information needs. The aim of this study is to investigate what context information the human analyst needs. We used design science research, in which we conducted interviews with ten practitioners in the traceability area to understand the information needed by human analysts. We then compared the information collected from the interviews with existing literature. We created a prototype tool that presents this information to the human analyst. To further understand the role of context information, we conducted a controlled experiment with 33 participants. Our interviews reveal that human analysts need information from three different sources: 1) from the artifacts connected by the link, 2) from the traceability information model, and 3) from the tracing algorithm. The experiment results show that the content of the connected artifacts is more useful to the analyst than the contextual information of the artifacts.
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