一句话：对多个广泛使用的 Python 静态调用图工具进行定量与定性对比，发现构造效果差异显著且仍有改进空间。
随着 Python 的广泛应用，针对 Python 代码的分析工作愈发重要，而许多静态分析算法都依赖调用图的构建。本文对若干广泛使用的 Python 静态调用图工具进行了定量与定性的对比实证分析，考察其构建效果。实验表明，现有 Python 静态调用图工具在构造有效性上存在较大差异，整体仍有改进空间。该研究为理解现有工具的能力边界和后续改进提供了实证依据。
In recent years, the extensive application of the Python language has made its analysis work more and more valuable. Many static analysis algorithms need to rely on the construction of call graphs. In this paper, we did a comparative empirical analysis of several widely used Python static call graph tools both quantitatively and qualitatively. Experiments show that the existing Python static call graph tools have a large difference in the construction effectiveness, and there is still room for improvement.
DOI 原文 ·
@inproceedings{paperbot5181,
title = {Empirical Study of Python Call Graph},
author = {Li Yu},
booktitle = {ASE},
year = {2019},
doi = {10.1109/ase.2019.00160}
}