Using a Cognitive Psychology Perspective on Errors to Improve Requirements Quality: An Empirical Investigation
Using a Cognitive Psychology Perspective on Errors to Improve Requirements Quality: An Empirical Investigation
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使用认知心理学视角看待错误来提高需求质量：一项实证研究
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发表时间：
2016
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通讯作者：
Gary L. Bradshaw
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作者：
Vaibhav Anu;G. Walia;Wenhua Hu;Jeffrey C. Carver;Gary L. Bradshaw
软件检查是一种有效的方法，用于早日检测软件开发工件中存在的故障（例如，需求和设计文档）。但是，由于缺乏对基本故障来源的关注（即，是什么原因导致了故障的是什么？），许多故障未被发现。为了解决这个问题，心理学家在分析人类认知失败（即人错误）方面所做的研究工作正在研究中使用，以帮助检查员在要求文档中检测错误和相应的错误（错误表现）。我们假设使用人类错误的形式分类法（故障的根本来源）时，故障检测性能将表现出显着的收益。本文介绍了新开发的人类错误分类法（HET）和正式的错误检查和检查过程（EAI），以提高要求检查过程中检查员的故障检测性能。一项受控的经验研究评估了HET和EAI与基于故障的检查相比的实用性。结果验证了我们的假设，并为常见发生的人类错误提供了有用的见解，这导致了需求故障以及进一步完善HET和EAI过程的领域。
Software inspections are an effective method for early detection of faults present in software development artifacts (e.g., requirements and design documents). However, many faults are left undetected due to the lack of focus on the underlying sources of faults (i.e., what caused the injection of the fault?). To address this problem, research work done by Psychologists on analyzing the failures of human cognition (i.e., human errors) is being used in this research to help inspectors detect errors and corresponding faults (manifestations of errors) in requirements documents. We hypothesize that the fault detection performance will demonstrate significant gains when using a formal taxonomy of human errors (the underlying source of faults). This paper describes a newly developed Human Error Taxonomy (HET) and a formal Error-Abstraction and Inspection (EAI) process to improve fault detection performance of inspectors during the requirements inspection. A controlled empirical study evaluated the usefulness of HET and EAI compared to fault based inspection. The results verify our hypothesis and provide useful insights into commonly occurring human errors that contributed to requirement faults along with areas to further refine both the HET and the EAI process.