Process mining multiple repositories for software defect resolution from control and organizational perspective

Monika Gupta, A. Sureka, S. Padmanabhuni
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引用次数: 38

Abstract

Issue reporting and resolution is a software engineering process supported by tools such as Issue Tracking System (ITS), Peer Code Review (PCR) system and Version Control System (VCS). Several open source software projects such as Google Chromium and Android follow process in which a defect or feature enhancement request is reported to an issue tracker followed by source-code change or patch review and patch commit using a version control system. We present an application of process mining three software repositories (ITS, PCR and VCS) from control flow and organizational perspective for effective process management. ITS, PCR and VCS are not explicitly linked so we implement regular expression based heuristics to integrate data from three repositories for Google Chromium project. We define activities such as bug reporting, bug fixing, bug verification, patch submission, patch review, and source code commit and create an event log of the bug resolution process. The extracted event log contains audit trail data such as caseID, timestamp, activity name and performer. We discover runtime process model for bug resolution process spanning three repositories using process mining tool, Disco, and conduct process performance and efficiency analysis. We identify bottlenecks, define and detect basic and composite anti-patterns. In addition to control flow analysis, we mine event log to perform organizational analysis and discover metrics such as handover of work, subcontracting, joint cases and joint activities.
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从控制和组织的角度为软件缺陷解决挖掘多个存储库的过程
问题报告和解决是一个软件工程过程,由诸如问题跟踪系统(ITS)、对等代码审查系统(PCR)和版本控制系统(VCS)等工具支持。一些开源软件项目,如Google Chromium和Android,都遵循这样的流程:将缺陷或功能增强请求报告给问题跟踪器,然后使用版本控制系统进行源代码更改或补丁审查和补丁提交。我们从控制流和组织的角度提出了过程挖掘三个软件存储库(ITS, PCR和VCS)的应用,以实现有效的过程管理。ITS, PCR和VCS没有显式链接,因此我们实现了基于正则表达式的启发式方法来集成来自Google Chromium项目的三个存储库的数据。我们定义诸如错误报告、错误修复、错误验证、补丁提交、补丁审查和源代码提交等活动,并创建错误解决过程的事件日志。提取的事件日志包含审计跟踪数据,如caseID、时间戳、活动名称和执行者。我们使用过程挖掘工具Disco发现跨越三个存储库的错误解决过程的运行时过程模型,并进行过程性能和效率分析。我们识别瓶颈,定义和检测基本和复合反模式。除控制流分析外,我们还挖掘事件日志进行组织分析,发现工作移交、分包、联合案例和联合活动等指标。
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