一句话：提出通用高效的 Python 运行时验证工具 PyMOP，支持多逻辑多插桩，并在大规模测试中显著提速、发现真实缺陷。
Python 生态缺乏通用、高效且可扩展的运行时验证工具，现有工具常局限于特定领域或规约逻辑，且速度较慢。本文提出 PyMOP，一个面向 Python 的通用可扩展运行时验证工具，支持五种逻辑、五种监控算法、81 个规约和三种插桩策略。作者在 839 个 GitHub 项目的 48,090 个单元测试上评估，发现 PyMOP 比两个近期动态分析工具最高快 419.23 倍；昂贵插桩是 Python 运行时验证开销的主要来源；共发现 156 个缺陷，其中 84 个被开发者确认或修复。PyMOP 的通用性与效率为 Python 运行时验证的后续进展提供了良好平台。
Runtime verification (RV) now scales for testing in thousands of open-source Java projects, helping find hundreds of bugs by monitoring test executions against formal specifications (specs). The popular Python ecosystem could use such benefits. But, current Python RV tools are limited to a domain or spec logic, or they are slow. We present PyMOP, a generic, extensible, and more efficient Python RV tool. PyMOP supports five logics, implements five monitoring algorithms, ships with 81 specs, and supports three instrumentation strategies. On 48,090 unit tests in 839 GitHub projects, we find mainly that (i) PyMOP is up to 419.23x faster than two recent dynamic analysis tools; (ii) Expensive instrumentation is a main cause of RV's runtime overhead for Python; and (iii) 84 of 156 bugs that PyMOP found were confirmed or fixed by developers. PyMOP's genericness and efficiency position it well as an excellent platform for the next advances on RV for Python. PyMOP is at https://github.com/SoftEngResearch/pymop and a video demo is at https://pymop.zhuohangshen.com/demo.
@inproceedings{ShenYGSdL26,
title = {PyMOP: A Runtime Verification Tool for Python},
author = {Zhuohang Shen and Mohammed Yaseen and Kevin Guan and Denini Silva and Marcelo d'Amorim and Owolabi Legunsen},
booktitle = {FSE},
year = {2026},
doi = {10.1145/3803437.3806424}
}