Eclipse与Mozilla:两个大型开源问题报告存储库的比较

Sean Banerjee, Jordan Helmick, Zahid A. Syed, B. Cukic
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引用次数: 11

摘要

Bug跟踪系统在大型软件系统的开发和维护中起着重要的作用。有了开源漏洞跟踪系统,研究人员可以利用丰富的数据集,提出解决方案来管理重复的报告分类、开发人员分配和质量评估。尽管研究取得了进展,但我们对这些存储库内容的理解仍然有限,主要是因为它们的大小。在许多情况下,研究人员分析数据集的一小部分,从而限制了对问题报告动态的理解。本研究的目的是探索两个大型开源问题报告存储库的属性。在下载时,Eclipse数据集包含363个;770个报告跨越11年以上,而Mozilla包含699个;085份报告,跨度超过14年。我们的研究通过分析存储库中的变化和提交问题报告的用户的配置文件来检查数据集随时间的演变。我们提供了定量的证据,证明提交者的成熟度如何减少提交低质量、无关紧要或重复报告的倾向。我们表明,多样化的用户基础(Mozilla的特点)给开发团队带来了挑战,因为他们花了更多的时间来分类,而不是解决问题。最后,我们为研究社区提供了一系列关于如何研究大规模问题存储库的观察和建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eclipse vs. Mozilla: A Comparison of Two Large-Scale Open Source Problem Report Repositories
Bug tracking systems play an important role in the development and maintenance of large-scale software systems. Having access to open source bug tracking systems has allowed researchers to take advantage of rich datasets and propose solutions to manage duplicate report classification, developer assignment and quality assessment. In spite of research advances, our understanding of the content of these repositories remains limited, primarily because of their size. In many cases, researchers analyze small portions of datasets thus limiting the understanding of the dynamics of problem reporting. The objective of this study is to explore the properties of two large-scale open source problem report repositories. The Eclipse dataset, at the time of download, consisted of 363; 770 reports spanning 11+ years, whereas Mozilla contained 699; 085 reports spanning 14+ years.Our research examines the evolution of datasets over time by analyzing the changes in the repository and the profiles of users who submit problem reports. We provide quantitative evidence on how submitter's maturity reduces the propensity to submit poor quality, insignificant or duplicate reports. We show that a diverse user base, characteristic of Mozilla, creates challenges for the development team as they spend more time triaging, rather than fixing, issues. Finally, we provide the research community with a series of observations and suggestions on how to study large-scale problem repositories.
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