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Towards Understanding How Developers Spend Their Effort during Maintenance Activities

机译:为了了解开发人员在维护活动期间如何努力

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For many years, researchers and practitioners have strived to assess and improve the productivity of software development teams. One key step toward achieving this goal is the understanding of factors affecting the efficiency of developers performing development and maintenance activities. In this paper, we aim to understand how developers’ spend their effort during maintenance activities and study the factors affecting developers’ effort. By knowing how developers’ spend their effort and which factors affect their effort, software organisations will be able to take the necessary steps to improve the efficiency of their developers, for example, by providing them with adequate program comprehension tools. For this preliminary study, we mine 2,408 developers’ interaction histories and 3,395 patches from four open-source software projects (ECF, Mylyn, PDE, Eclipse Platform). We observe that usually, the complexity of the implementation required for a task does not reflect the effort spent by developers on the task. Most of the effort appears to be spent during the exploration of the program. In average, 62% of files explored during the implementation of a task are not significantly relevant to the final implementation of the task. Developers who explore a large number of files that are not significantly relevant to the solution to their task take a longer time to perform the task. We expect that the results of this study will pave the way for better program comprehension tools to guide developers during their explorations of software systems.
机译:多年来,研究人员和从业者致力于评估和提高软件开发团队的生产力。为实现这一目标的一个关键步骤是影响开发商进行开发和维护活动的效率因素的理解。在本文中,我们的目标是了解开发商的维护活动期间的花费他们的努力和研究影响发展的因素的努力。通过了解开发人员如何度过努力以及哪些因素影响他们的努力,软件组织将能够采取必要的步骤来提高开发人员的效率,例如,通过为他们提供足够的计划理解工具。对于初步研究,我们可以从四个开源软件项目(ECF,Mylyn,PDE,Eclipse平台)中挖掘2,408个开发人员的交互历史和3,395个补丁。我们观察到,通常,任务所需的实现的复杂性并未反映开发人员在任务上所花费的努力。大多数努力似乎在探索该计划期间花费。平均而言,在执行任务期间探讨的62%的文件与任务的最终实施没有明显相关。开发人员探索与其任务的解决方案没有显着相关的大量文件需要更长的时间来执行任务。我们预计本研究的结果将为更好的计划理解工具铺平道路,以指导开发人员在探索软件系统期间。

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