PyRadar: Towards Automatically Retrieving and Validating Source Code Repository Information for PyPI Packages
Kai Gao, Weiwei Xu, Wenhao Yang, Minghui Zhou
摘要
A package's source code repository records the package's development history, which is critical for the use and risk monitoring of the package. However, a package release often misses its source code repository due to the separation of the package's development platform from its distribution platform. To establish the link, existing tools retrieve the release's repository information from its metadata, which suffers from two limitations: the metadata may not contain or contain wrong information. Our analysis shows that existing tools can only retrieve repository information for up to 70.5% of PyPI releases. To address the limitations, this paper proposes PyRadar, a novel framework that utilizes the metadata and source distribution to retrieve and validate the repository information for PyPI releases. We start with an empirical study to compare four existing tools on 4,227,425 PyPI releases and analyze phantom files (files appearing in the release's distribution but not in the release's repository) in 14,375 correct and 2,064 incorrect package-repository links. Based on the findings, we design PyRadar with three components, i.e., Metadata-based Retriever, Source Code Repository Validator, and Source Code-based Retriever, that progressively retrieves correct source code repository information for PyPI releases. In particular, the Metadata-based Retriever combines best practices of existing tools and successfully retrieves repository information from the metadata for 72.1% of PyPI releases. The Source Code Repository Validator applies common machine learning algorithms on six crafted features and achieves an AUC of up to 0.995. The Source Code-based Retriever queries World of Code with the SHA-1 hashes of all Python files in the release's source distribution and retrieves repository information for 90.2% of packages in our dataset with an accuracy of 0.970. Both practitioners and researchers can employ the PyRadar to better use PyPI packages.
CCS Concepts: • Software and its engineering → Software libraries and repositories; Maintaining software; • Human-centered computing → Open source software.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper2
- Licoeval: Evaluating LLMs on License Compliance in Code GenerationWeiwei Xu, Kai Gao, Hao He, Minghui ZhouICSE 2025 · 被引用 6 次
- PyFEX: Uncovering Evasive Python-based Threats via Resilient and Exhaustive Path ExplorationMeng Wang, Yue Ma, Majid Garoosi, Wenting Fan 等CCS 2026
它引用的顶会 Paper15
- Small World with High Risks: A Study of Security Threats in the npm EcosystemMarkus Zimmermann, Cristian-Alexandru Staicu, Cam Tenny, Michael PradelUSENIX Security 2019 · 被引用 281 次
- Demystifying the Vulnerability Propagation and Its Evolution via Dependency Trees in the NPM EcosystemChengwei Liu, Sen Chen, Lingling Fan, Bihuan Chen 等ICSE 2022 · 被引用 94 次
- What Makes a Good Commit Message?Yingchen Tian, Yuxia Zhang, Klaas-Jan Stol, Lin Jiang 等ICSE 2022 · 被引用 90 次
- Selecting third-party libraries: the practitioners' perspectiveEnrique Larios Vargas, Maurício Finavaro Aniche, Christoph Treude, Magiel Bruntink 等FSE 2020 · 被引用 81 次
- Watchman: monitoring dependency conflicts for Python library ecosystemYing Wang, Ming Wen, Yepang Liu, Yibo Wang 等ICSE 2020 · 被引用 65 次
相关 Paper
- Uncovering Similar but Different Packages in PyPI and Potential Security ThreatsSunha Park, Soojin Han, Seunghoon WooFSE 2026
- An Empirical Study of Malicious Code In PyPI EcosystemWenbo Guo, Zhengzi Xu, Chengwei Liu, Cheng Huang 等ASE 2023 · 被引用 31 次
- Cutting the Gordian Knot: Detecting Malicious PyPI Packages via a Knowledge-Mining FrameworkWenbo Guo, Chengwei Liu, Ming Kang, Yiran Zhang 等USENIX Security 2026 · 被引用 1 次
- Less is More? An Empirical Study on Configuration Issues in Python PyPI EcosystemYun Peng, Ruida Hu, Ruoke Wang, Cuiyun Gao 等ICSE 2024 · 被引用 5 次
- Fixing dependency errors for Python build reproducibilitySuchita Mukherjee, Abigail Almanza, Cindy Rubio-GonzálezISSTA 2021 · 被引用 55 次
