R包生态系统的实证分析
An Empirical Analysis of the R Package Ecosystem
摘要：
在这项研究中，我们对R包生态系统进行了全面的纵向经验总结，不仅包括CRAN，还包括Bioconductor和GitHub。我们分析了20年来超过25，000个软件包、150，000个版本和1500万个文件，为软件包、版本、作者、许可证和其他重要元数据的通用指标提供了全面的统计和趋势。我们发现，生态系统的历史增长在所有指标下都是强劲的，活跃软件包的复合年增长率为29%，新版本为28%，活跃维护人员为26%。与许多类似的社会系统一样，我们发现了一些具有实际意义的高度右偏分布，包括每个软件包的发布分布，每个作者或维护者的软件包和发布，软件包和维护者的依赖程度，以及每个软件包和发布的大小。例如，前五个软件包被导入了近25%的软件包，前十个维护者支持的软件包被导入了超过一半的软件包。我们还强调了生态系统的动态性质，记录了R的增长的急剧加速和显着减速。从许可的角度来看，我们发现绝大多数软件包都是在copyleft许可下发布的，或者完全省略了许可信息。本文中的数据、方法和计算为与R和CRAN相关的公共讨论和行业决策提供了一个锚点，为未来更广泛地研究R软件生态系统和“数据科学”奠定了基础。
英文摘要：
In this research, we present a comprehensive, longitudinal empirical summary of the R package ecosystem, including not just CRAN, but also Bioconductor and GitHub. We analyze more than 25,000 packages, 150,000 releases, and 15 million files across two decades, providing comprehensive counts and trends for common metrics across packages, releases, authors, licenses, and other important metadata. We find that the historical growth of the ecosystem has been robust under all measures, with a compound annual growth rate of 29% for active packages, 28% for new releases, and 26% for active maintainers. As with many similar social systems, we find a number of highly right-skewed distributions with practical implications, including the distribution of releases per package, packages and releases per author or maintainer, package and maintainer dependency in-degree, and size per package and release. For example, the top five packages are imported by nearly 25% of all packages, and the top ten maintainers support packages that are imported by over half of all packages. We also highlight the dynamic nature of the ecosystem, recording both dramatic acceleration and notable deceleration in the growth of R. From a licensing perspective, we find a notable majority of packages are distributed under copyleft licensing or omit licensing information entirely. The data, methods, and calculations herein provide an anchor for public discourse and industry decisions related to R and CRAN, serving as a foundation for future research on the R software ecosystem and "data science" more broadly.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
