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Mining Individual Performance Indicators in Collaborative Development Using Software Repositories

机译:使用软件存储库在协作开发中挖掘个人绩效指标

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A better understanding of the individual developers’ performance has been shown to result in benefits such as improved project estimation accuracy and enhanced software quality assurance. However, new challenges of distinguishing the individual activities involved in software evolution arise when considering collaborative development environments. Since Software repositories such as version control systems (VCS) and bug tracking systems (BTS) are available for most software projects and hold a detailed and rich record of the historical development information, this paper presents our experiences mining individual performance indicators in collaborative development environments by using these repositories. The base of our key idea is to identify the complexity metrics (in the code base) and field defects(from bug tracking system) at individual-level by incorporating the historical data from version control system. We also remotely measure and analyze these indicators mined from a libre project jEdit, which involves around one hundred developer. The results show that these indicators are feasible and instructive in the understanding of the individual performance.
机译:更好地了解各个开发人员的性能,已显示出导致更好的项目估计准确性和增强的软件质量保证等益处。然而,在考虑合作开发环境时出现区分涉及软件演变的个人活动的新挑战。由于Version Control系统(VCS)和Bug跟踪系统(BTS)等软件存储库可用于大多数软件项目,并持有历史发展信息的详细和丰富的记录,本文提出了我们在协作开发环境中采矿的各个绩效指标的经验使用这些存储库。我们的关键思想的基础是通过从版本控制系统中包含历史数据来识别各个级别的复杂性度量(在代码基础上)和字段缺陷(来自错误跟踪系统)。我们还远程衡量并分析来自Libre项目Jedit的这些指标,涉及大约一百名开发人员。结果表明,这些指标在对个人表现的理解方面是可行和有益的。

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