重新发现数据集：连接重复报表
Rediscovery Datasets: Connecting Duplicate Reports
摘要：
同一个缺陷可能会被多个客户端重新发现，从而导致计划外停机，降低客户满意度。在流行的开放源码软件的情况下，定期报告大量缺陷。这些报告中有大量实际上是彼此重复/重新发现的。研究人员分析了过去与重复缺陷报告内容相关的因素。然而，其他一些潜在的重要因素，如重复缺陷报告之间的相互关系，在缺陷跟踪系统（如Bugzilla）中并不容易获得。这些信息可以加快错误修复，使有效的分类，提高客户档案等，在本文中，我们提出了三个缺陷重新发现数据集挖掘Bugzilla。这些数据集捕获三组开源软件项目的数据：Apache、Eclipse和KDE。这些数据集包含18年（1999-2017）期间约91.4万份缺陷报告的信息，以捕获重复缺陷之间的相互关系。我们相信，与社区共享这些数据将有助于研究人员和从业人员更好地理解缺陷重新发现的本质，并增强对缺陷报告的分析。
英文摘要：
The same defect can be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. In the case of popular open source software, high volume of defects is reported on a regular basis. A large number of these reports are actually duplicates / rediscoveries of each other. Researchers have analyzed the factors related to the content of duplicate defect reports in the past. However, some of the other potentially important factors, such as the inter-relationships among duplicate defect reports, are not readily available in defect tracking systems such as Bugzilla. This information may speed up bug fixing, enable efficient triaging, improve customer profiles, etc. In this paper, we present three defect rediscovery datasets mined from Bugzilla. The datasets capture data for three groups of open source software projects: Apache, Eclipse, and KDE. The datasets contain information about approximately 914 thousands of defect reports over a period of 18 years (1999-2017) to capture the inter-relationships among duplicate defects. We believe that sharing these data with the community will help researchers and practitioners to better understand the nature of defect rediscovery and enhance the analysis of defect reports.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
