Characterizing and detecting Python version incompatibilities caused by inconsistent version specifications

IF 3.7 2区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Journal of Systems and Software Pub Date : 2025-01-14 DOI:10.1016/j.jss.2025.112337

Shuo Li , Haocheng Gao , Wei Chen , Yi Li , Haoxiang Tian , Chengwei Liu , Dan Ye

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引用次数: 0

Abstract

Python interpreter serves as the foundation for developing Python projects. Configuring compatible Python version is essential for packaging and reusing third-party libraries (TPLs) in the Python ecosystem. When the Python distribution version range constraint of a third-party library is incorrectly declared, it may lead to installation failures or runtime errors when the library is used by a client project. We call such errors Python Distribution Version Specification Error (PDSpecErr). PDSpecErrs are not studied adequately and there still lacks a method to guarantee the correctness of Python version specifications. To combat PDSpecErrs and mitigate their adverse impacts on downstream applications, we conducted the first exploratory study on 3000 real-world TPLs to investigate PDSpecErrs about their prevalence, symptom categories, and diagnostic patterns. Based on the comprehensive study, we designed and implemented PyChecker, a tool to automatically detect PDSpecErrs in TPLs, locate root causes, and generate fixing solutions. We evaluated PyChecker on 3000 TPL releases and PyChecker detected 842 PDSpecErrs, reporting their root causes and recommending fixing solutions. We have reported 52 PDSpecErrs to the concerned developers. So far, 32 issues have been confirmed and fixed according to our suggestions.

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来源期刊

Journal of Systems and Software 工程技术-计算机：理论方法

CiteScore

8.60

自引率

5.70%

发文量

193

审稿时长

16 weeks

期刊介绍： The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to: •Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution •Agile, model-driven, service-oriented, open source and global software development •Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems •Human factors and management concerns of software development •Data management and big data issues of software systems •Metrics and evaluation, data mining of software development resources •Business and economic aspects of software development processes The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.