AutoMetric: Towards Measuring Open-Source Software Quality Metrics Automatically

Taejun Lee, Heewon Park, Heejo Lee
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Abstract

In modern software development, open-source software (OSS) plays a crucial role. Although some methods exist to verify the safety of OSS, the current automation technologies fall short. To address this problem, we propose AutoMetric, an automatic technique for measuring security metrics for OSS in repository level. Using AutoMetric which only collects repository addresses of the projects, it is possible to inspect many projects simultaneously regardless of its size and scope. AutoMetric contains five metrics: Mean Time to Update (MU), Mean Time to Commit (MC), Number of Contributors (NC), Inactive Period (IP), and Branch Protection (BP). These metrics can be calculated quickly even if the source code changes. By comparing metrics in AutoMetric with 2,675 reported vulnerabilities in GitHub Advisory Database (GAD), the result shows that the more frequent updates and commits and the shorter the inactivity period, the more vulnerabilities were found.
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自动化度量:朝着自动度量开源软件质量度量的方向发展
在现代软件开发中,开源软件(OSS)起着至关重要的作用。虽然存在一些方法来验证OSS的安全性,但目前的自动化技术还远远不够。为了解决这个问题,我们提出了AutoMetric,这是一种用于在存储库级别度量OSS安全度量的自动技术。使用AutoMetric只收集项目的存储库地址,可以同时检查许多项目,而不考虑其大小和范围。AutoMetric包含五个度量:平均更新时间(MU)、平均提交时间(MC)、贡献者数量(NC)、非活动周期(IP)和分支保护(BP)。即使源代码更改,也可以快速计算出这些度量。通过将AutoMetric中的指标与GitHub Advisory Database (GAD)中报告的2675个漏洞进行比较,结果表明,更新和提交越频繁,不活跃时间越短,发现的漏洞就越多。
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