Fri 19 Jul 2024 10:30 - 11:00 at Lounge - Poster Session 4

A package’s source code repository records the development history of the package, providing indispensable information 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 the release’s metadata, which, however, suffers from two limitations: the metadata may not contain or contain the wrong information. Our analysis shows that existing tools can only retrieve repository information for up to 70.5% of PyPI releases (63.1% of packages). To address the limitations, this paper proposes \textsc{PyRadar}, a novel framework that utilizes both the release’s metadata and source code to automatically retrieve and validate the repository information for PyPI package releases. We start with an empirical study to compare four existing metadata-based tools on 4,227,425 PyPI releases and analyze phantom files (files appearing in the release distribution but not in the release’s repository) in 14,375 correct package-repository links and 2,064 incorrect links. Based on the findings, we design \textsc{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 the 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 machine learning models on six crafted features and achieves an AUC of up to 0.995. The Source Code-based Retriever queries \textit{World of Code} with the SHA-1 hash of 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 \textsc{PyRadar} to better use PyPI packages.

Fri 19 Jul

Displayed time zone: Brasilia, Distrito Federal, Brazil change

10:30 - 11:00
Poster Session 4Posters at Lounge
10:30
30m
Poster
Understanding the Impact of APIs Behavioral Breaking Changes on Client Applications
Posters
Dhanushka Jayasuriya University of Auckland, Valerio Terragni University of Auckland, Jens Dietrich Victoria University of Wellington, Kelly Blincoe University of Auckland
10:30
30m
Poster
Your Code Secret Belongs to Me: Neural Code Completion Tools Can Memorize Hard-coded Credentials
Posters
Yizhan Huang The Chinese University of Hong Kong, Yichen LI The Chinese University of Hong Kong, Weibin Wu Sun Yat-sen University, Jianping Zhang The Chinese University of Hong Kong, Michael Lyu The Chinese University of Hong Kong
10:30
30m
Poster
Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models
Posters
Yan Wang Central University of Finance and Economics, Xiaoning Li Central University of Finance and Economics, Tien N. Nguyen University of Texas at Dallas, Shaohua Wang Central University of Finance and Economics, Chao Ni School of Software Technology, Zhejiang University, Ling Ding Central University of Finance and Economics
10:30
30m
Poster
PyRadar: Towards Automatically Retrieving and Validating Source Code Repository Information for PyPI Packages
Posters
Kai Gao Peking University, Weiwei Xu Peking University, Wenhao Yang Peking University, Minghui Zhou Peking University
10:30
30m
Poster
"The Law Doesn’t Work Like a Computer": Exploring Software Licensing Issues Faced by Legal Practitioners
Posters
Nathan Wintersgill William & Mary, Trevor Stalnaker William & Mary, Laura A. Heymann William & Mary, Oscar Chaparro William & Mary, Denys Poshyvanyk William & Mary
10:30
30m
Poster
RavenBuild: Context, Relevance, and Dependency Aware Build Outcome Prediction
Posters
Gengyi Sun University of Waterloo, Sarra Habchi Ubisoft Montréal, Shane McIntosh University of Waterloo
10:30
30m
Poster
MirrorFair: Fixing Fairness Bugs in Machine Learning Software via Counterfactual Predictions
Posters
Ying Xiao King's College London / Southern University of Science and Technology, Jie M. Zhang King's College London, Yepang Liu Southern University of Science and Technology, Mohammad Reza Mousavi King's College London, Sicen Liu Southern University of Science and Technology, Dingyuan Xue Southern University of Science and Technology
10:30
30m
Poster
Do Code Generation Models Think Like Us? - A Study of Attention Alignment between Large Language Models and Human Programmers
Posters
Bonan Kou Purdue University, Shengmai Chen Purdue University, Zhijie Wang University of Alberta, Lei Ma The University of Tokyo & University of Alberta, Tianyi Zhang Purdue University
10:30
30m
Poster
Dependency-Induced Waste in Continuous Integration: An Empirical Study on NPM Dependencies
Posters
Nimmi Weeraddana University of Waterloo, Mahmoud Alfadel University of Waterloo, Shane McIntosh University of Waterloo
10:30
30m
Poster
A Miss Is as Good as A Mile: Metamorphic Testing for Deep Learning Operators
Posters
Jinyin Chen Zhejiang University of Technology, Chengyu Jia Zhejiang University of Technology, Yunjie Yan Zhejiang University of Technology, Jie Ge Zhejiang University of Technology, haibin zheng Zhejiang University of Technology, Yao Cheng TÜV SÜD Asia Pacific Pte. Ltd.
10:30
30m
Poster
Investigating Documented Privacy Changes in Android OS
Posters
Chuan Yan University of Queensland, Mark Huasong Meng National University of Singapore, Fuman Xie University of Queensland, Guangdong Bai University of Queensland
10:30
30m
Poster
Analyzing Quantum Programs with LintQ: A Static Analysis Framework for Qiskit
Posters
Matteo Paltenghi University of Stuttgart, Michael Pradel University of Stuttgart
10:30
30m
Poster
Generative AI for Pull Request Descriptions: Adoption, Impact, and Developer Interventions
Posters
Tao Xiao Nara Institute of Science and Technology, Hideaki Hata Shinshu University, Christoph Treude Singapore Management University, Kenichi Matsumoto Nara Institute of Science and Technology
10:30
30m
Poster
Bloat beneath Python's Scales: A Fine-Grained Inter-Project Dependency Analysis
Posters
Georgios-Petros Drosos ETH Zurich, Thodoris Sotiropoulos ETH Zurich, Diomidis Spinellis Athens University of Economics and Business & Delft University of Technology, Dimitris Mitropoulos University of Athens

Information for Participants
Fri 19 Jul 2024 10:30 - 11:00 at Lounge - Poster Session 4
Info for room Lounge:

This room is conjoined with the Foyer to provide additional space for the coffee break, and hold poster presentations throughout the event.