一个通过时态知识图集成自述和提交的工具

Akhila Sri Manasa Venigalla, Mir Sameed Ali, Nikhil Manjunath, S. Chimalakonda
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引用次数: 0

摘要

自述文件和提交日志携带重要和有用的项目信息,与项目依赖项、项目功能、添加、删除等相对应。这两个工件已经分别进行了分析,以获得与贡献指南、bug预测和定位相对应的项目特定信息。将自述文件与相关的提交链接起来,并进一步查询链接的数据,可以帮助评估对自述文件所做的特定于时间戳的更改。利用知识图表示数据,可以在很大程度上支持异构源数据的查询、集成和提取。为此,我们提出了一个工具来生成特定于自述文件的时态知识图,作为集成自述文件和提交日志的第一步。由于提交包含更改的时间信息,我们看到将这些信息覆盖在自述文件中的相应文本上可以帮助到达一个时间知识图(TKG)。我们提供了一个针对一个存储库查询TKG的案例研究,并进一步在GitHub上跨越10种编程语言的10个存储库上评估该工具。观看演示视频,请访问- https://youtu.be/4YOCDngf4bY。工具网站:- https://akhilasrimanasa.github.io/rcgraph/
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RCGraph - A Tool to Integrate Readme and Commits through Temporal Knowledge Graphs
Readme files and commit logs carry important and useful project information, corresponding to project dependencies, project functionalities, additions, deletions, and so on. These two artifacts have been analysed separately to obtain project specific information corresponding to contribution guidelines, bug prediction and localisation. Linking the readme files with associated commits and further querying the linked data could help in assessing time stamp specific changes made to the readme files. Utilizing knowledge graph representation of data is observed to largely support querying and integration and extraction of data from heterogeneous sources. To this end, we present a tool to generate readme specific temporal knowledge graph, as a first step towards integrating readme files and commit logs. As commits contain temporal information of the changes, we see that overlaying this information over the corresponding text in readme files could help in arriving at a temporal knowledge graph (TKG). We present a case study of querying the TKG for one repository and further evaluate the tool on 10 repositories spanning across 10 programming languages on GitHub. For demo video, visit - https://youtu.be/4YOCDngf4bY. For website of the tool, visit - https://akhilasrimanasa.github.io/rcgraph/
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