Characterizing and Predicting Mental Fatigue during Programming Tasks
Characterizing and Predicting Mental Fatigue during Programming Tasks
复制标题
表征和预测编程任务期间的精神疲劳
DOI：
--
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Chris Parnin
中科院分区：
文献类型：
--
作者：
Saurabh Sarkar;Chris Parnin
精神疲劳会降低一个人的认知能力和身体能力。在需要持续注意力的任务中，例如驾驶，疲劳是众所周知的风险。然而，当在编程等日常任务中感到疲劳时，风险的性质更加分散和累积，但后果可能同样严重（例如自动驾驶软件中的缺陷）。在方案拟订的背景下查明疲劳的风险，可以导致采取干预措施，防止引入缺陷，并引入应对机制。为了描述和预测这些风险，我们进行了两项研究：一项调查研究，我们要求311名软件开发人员评估他们疲劳的严重程度和频率，并回忆最近编程时疲劳的经历;另一项观察性研究，9名专业软件开发人员调查从交互历史预测疲劳的可行性。从调查中，我们发现大多数开发人员报告了严重（66%）和频繁（59%）的疲劳问题。此外，我们将他们的经历归类为对编程任务的七种影响，其中包括动机降低和处理涉及大量脑力工作的任务的能力降低。从我们的观察性研究中，我们的结果发现了几种测量方法，如专注时间，按键时间，错误率和软件质量警告的增加，可以用于检测疲劳水平。这些结果旨在支持开发人员和行业提高软件质量和软件开发人员的工作条件。
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.
DOI：
10.1111/j.1547-5069.1999.tb00420.x
发表时间：
1999-03
期刊：
Image--the journal of nursing scholarship
影响因子：
--
作者：
L. Aaronson;C. Teel;V. Cassmeyer;G. Neuberger;L. Pallikkathayil;J. Pierce;A. Press;P. D. Williams;A. Wingate
通讯作者：
L. Aaronson;C. Teel;V. Cassmeyer;G. Neuberger;L. Pallikkathayil;J. Pierce;A. Press;P. D. Williams;A. Wingate