从开发日志中跟踪bug的自动化:一个基于开源软件的研究

Bilyaminu Auwal Romo, A. Capiluppi
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引用次数: 5

摘要

上下文:几乎在每个开源项目中,缺陷的信息和跟踪都是严重不完整的,导致开发日志中缺陷的可追溯性降低(例如,版本控制提交日志)。特别是,当考虑开发人员将什么记录为他们的操作时,缺陷数据经常出现不同步。同步或完成错误存储库的缺失数据,以及详细描述开发人员操作的日志,将有利于经验软件工程研究的各个分支:软件故障预测、软件可靠性、可追溯性、软件质量、工作量和成本估计、错误预测和错误修复。目的:为开源软件项目设计一个框架,使开发日志和bug问题数据的同步和填补过程自动化。方法:我们用一个来自GitHub的OSS项目示例实例化框架,并通过解析、链接和填充在它们的bug问题数据和开发日志中发现的空白。UML图显示了将用于合并、链接和连接bug问题数据与开发数据的相关模块。结果:分析超过300个OSS项目的样本,我们观察到大约1/2的bug相关数据出现在开发日志或问题跟踪日志中:其余的数据从一个或另一个来源丢失。我们设计了一种自动化的方法,通过使用可用的数据来填补任何一个来源的空白,当使用注释bug的一种启发式方法时,我们成功地映射了分析项目的所有缺失数据。需要调查和实现其他启发式方法。结论:本文设计了一个用于经验软件工程的开发日志和bug数据同步框架,自动填补issue数据中开发日志和bug的缺失部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards an automation of the traceability of bugs from development logs: a study based on open source software
Context: Information and tracking of defects can be severely incomplete in almost every Open Source project, resulting in a reduced traceability of defects into the development logs (i.e., version control commit logs). In particular, defect data often appears not in sync when considering what developers logged as their actions. Synchronizing or completing the missing data of the bug repositories, with the logs detailing the actions of developers, would benefit various branches of empirical software engineering research: prediction of software faults, software reliability, traceability, software quality, effort and cost estimation, bug prediction and bug fixing. Objective: To design a framework that automates the process of synchronizing and filling the gaps of the development logs and bug issue data for open source software projects. Method: We instantiate the framework with a sample of OSS projects from GitHub, and by parsing, linking and filling the gaps found in their bug issue data, and development logs. UML diagrams show the relevant modules that will be used to merge, link and connect the bug issue data with the development data. Results: Analysing a sample of over 300 OSS projects we observed that around 1/2 of bug-related data is present in either development logs or issue tracker logs: the rest of the data is missing from one or the other source. We designed an automated approach that fills the gaps of either source by making use of the available data, and we successfully mapped all the missing data of the analysed projects, when using one heuristics of annotating bugs. Other heuristics need to be investigated and implemented. Conclusion: In this paper a framework to synchronise the development logs and bug data used in empirical software engineering was designed to automatically fill the missing parts of development logs and bugs of issue data.
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