Sonarlizer explorer:一个使用SonarQube挖掘Github项目和识别技术债务项的工具

Diogo Pina, A. Goldman, C. Seaman
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引用次数: 4

摘要

人工智能的进步和Python等编程语言中机器学习功能的实现,以及云服务,使研究人员能够应用方法来聚类和预测软件工程数据中的行为和模式。另一方面,这些方法需要大量的数据,以便在不同的上下文中具有较高的准确性。本文介绍Sonarlizer xexplorer:一个从公共GitHub项目中捕获大量技术债务项和代码度量的工具。Sonarlizer explorer由两个子工具组成。第一个是Github xexplorer,负责从初始项目中挖掘公共Github存储库。第二个是Sonarlizer,负责使用SonarQube进行项目分析。我们使用该工具超过4个月,收集了近46,000个公共Java项目的技术债务项和代码指标。此外,我们挖掘了超过5700万个存储库和400万用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sonarlizer Xplorer: a tool to mine Github projects and identify technical debt items using SonarQube
The advancement of artificial intelligence and the imple-mentation of machine learning capabilities in programming languages such as Python, along with cloud services, allow researchers to apply methods to cluster and predict behav-iors and patterns in software engineering data. On the other hand, these methods need a large amount of data in order to work with high accuracy in different contexts. This paper introduces Sonarlizer Xplorer: a tool that captures a large number of technical debt items and code metrics from pub-lic GitHub projects. Sonarlizer Xplorer is composed of two sub-tools. The first is Github Xplorer, responsible for mining public Github repositories from an initial project. The second is Sonarlizer, responsible for taking projects and analyzing them using SonarQube. We used the tool over four months, collecting technical debt items and code metrics on almost 46,000 public Java projects. In addition, we mined over 57 million repositories and 4 million users.
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