An Empirical Analysis of Cross-OS Portability Issues in Python Projects
Year: 2026
Type: conference-paper
Abstract: While Python is designed as a cross-platform language, real-world applications encounter portability failures when deployed across different operating systems. We present the first large-scale empirical study of cross-OS portability issues in Python, analyzing 2,042 open-source repositories using two complementary approaches: systematic cross-OS test re-execution and manual analysis of GitHub issues. Our cross-platform testing of 500 projects reveals that 11.2% exhibit OS-dependent test failures. Through systematic analysis of 240 GitHub issues, we confirm 102 genuine portability problems spanning 95 additional projects. We develop a comprehensive taxonomy identifying 7 primary failure categories—with file/directory operations, process management, and library dependencies being most prevalent—along with 24 distinct sub-categories, 15 diagnostic signatures, and 4 systematic repair patterns. Our evaluation reveals that existing static analysis tools provide minimal support for portability detection, while large language models achieve 40–79% accuracy in identifying issues and 50–77% success in generating fixes when provided with structured guidance. Through 33 contributed pull requests, we demonstrate practical applicability and developer acceptance (17 merged, zero rejected) of our findings.
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7171980224