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Characterizing and Predicting Mental Fatigue during Programming Tasks

机译:在编程任务期间表征和预测心理疲劳

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Mental fatigue reduces one's cognitive and physical abilities. In tasks requiring continuous attention, such as driving, fatigue is a well-known risk. However, when fatigued during daily tasks, such as programming, the nature of risk is more diffuse and accumulative, yet the consequences can be just as severe (e.g. defects in autopilot software). Identifying risks of fatigue in the context of programming can lead to interventions that prevent introduction of defects and introduce coping mechanisms. To character and predict these risks, we conducted two studies: a survey study in which we asked 311 software developers to rate the severity and frequency of their fatigue and to recall a recent experience of being fatigued while programming, and an observational study with 9 professional software developers to investigate the feasibility of predicting fatigue from interaction history. From the survey, we found that a majority of developers report severe (66%) and frequent (59%) issues with fatigue. Further, we categorized their experiences into seven effects on programming tasks, which include reduced motivation and reduced ability to handle tasks involving large mental workloads. From our observational study, our results found how several measures, such as focus duration, key press time, error rates, and increases in software quality warnings, may be applied for detecting fatigue levels. Together, these results aims to support developers and the industry for improving software quality and work conditions for software developers.
机译:精神疲劳可降低一个人的认知和身体能力。在需要持续注意的任务中,如驾驶,疲劳是一种众所周知的风险。然而,当在日常任务期间疲劳时,例如编程,风险的性质更加漫长和累积,但后果可能与自动驾驶的后果一样严重(例如,Autopilot软件中的缺陷)。在编程的背景下识别疲劳风险可能导致防止引入缺陷并引入应对机制的干预措施。为了性格并预测这些风险,我们进行了两项研究:一项调查研究,其中我们要求311软件开发人员对其疲劳的严重程度和频率评估,并回顾最近进行疲劳的经验,以及9名专业的观察研究软件开发人员探讨了从互动历史中预测疲劳的可行性。从调查开始,我们发现大多数开发商报告严重(66 %)和频繁(59 %)疲劳问题。此外,我们将其经验分类为对编程任务的七种影响,包括降低动机和减少处理涉及大型心理工作量的任务的能力。从我们的观察学习中,我们的结果发现了多种措施,例如焦点持续时间,关键媒体,误差率和软件质量警告增加,可以应用于检测疲劳水平。这些结果集中在一起,旨在支持开发人员和行业,以提高软件开发人员的软件质量和工作条件。

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