软件包生态系统中的下游依赖包群实证研究

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
IET Software Pub Date : 2024-04-30 DOI:10.1049/2024/4488412
Qing Qi, Jian Cao
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引用次数: 0

摘要

重点包装在包装生态系统中的作用对整个生态系统的发展至关重要,因为它们是其他包装所依赖的包装。然而,包装生态系统中依赖包群的演变尚未得到系统研究。在本研究中,我们研究了三个典型打包生态系统中的下游依赖包组(DDGs)--Rust 的 Cargo、Perl 的 Comprehensive Perl Archive Network 和 Ruby 的 RubyGems,以确定它们的特征和演变。我们还识别并分析了一种特殊类型的 DDG,即协作式下游依赖包组(CDDG),它需要共享贡献者。我们的研究结果表明,DDGs(尤其是 CDDGs)的整体发展与整个生态系统的状况是一致的,DDGs 和 CDDGs 的规模遵循幂律分布。此外,不同生态系统中焦点包与下游包之间的相互作用机制也不尽相同,但焦点包在 DDGs 和 CDDGs 的发展中始终起着主导作用。最后,我们根据 CDDGs 的特征研究了下一阶段 CDDGs 发展的预测模型,结果表明随机森林和梯度提升回归树达到了可接受的预测精度。我们在 https://github.com/onion616/DDG 网站上提供了用于分析的原始数据和脚本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An Empirical Study on Downstream Dependency Package Groups in Software Packaging Ecosystems

An Empirical Study on Downstream Dependency Package Groups in Software Packaging Ecosystems

The role of focal packages in packaging ecosystems is crucial for the development of the entire ecosystem, as they are the packages on which other packages depend. However, the evolution of dependency groups in packaging ecosystems has not been systematically investigated. In this study, we examine the downstream dependency package groups (DDGs) in three typical packaging ecosystems—Cargo for Rust, Comprehensive Perl Archive Network for Perl, and RubyGems for Ruby—to identify their features and evolution. We also identify and analyze a special type of DDG, the collaborative downstream dependency package group (CDDG), which requires shared contributors. Our findings show that the overall development of DDGs, particularly CDDGs, is consistent with the status of the whole ecosystem, and the size of DDGs and CDDGs follows a power law distribution. Furthermore, the interaction mechanisms between focal packages and downstream packages differ between ecosystems, but focal packages always play a leading role in the development of DDGs and CDDGs. Finally, we investigate predictive models for the development of CDDGs in the next stage based on their features, and our results show that random forest and Gradient Boosting Regression Tree achieve acceptable prediction accuracy. We provide the raw data and scripts used for our analysis at https://github.com/onion616/DDG.

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来源期刊
IET Software
IET Software 工程技术-计算机:软件工程
CiteScore
4.20
自引率
0.00%
发文量
27
审稿时长
9 months
期刊介绍: IET Software publishes papers on all aspects of the software lifecycle, including design, development, implementation and maintenance. The focus of the journal is on the methods used to develop and maintain software, and their practical application. Authors are especially encouraged to submit papers on the following topics, although papers on all aspects of software engineering are welcome: Software and systems requirements engineering Formal methods, design methods, practice and experience Software architecture, aspect and object orientation, reuse and re-engineering Testing, verification and validation techniques Software dependability and measurement Human systems engineering and human-computer interaction Knowledge engineering; expert and knowledge-based systems, intelligent agents Information systems engineering Application of software engineering in industry and commerce Software engineering technology transfer Management of software development Theoretical aspects of software development Machine learning Big data and big code Cloud computing Current Special Issue. Call for papers: Knowledge Discovery for Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_KDSD.pdf Big Data Analytics for Sustainable Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_BDASSD.pdf
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