Semantic-Enhanced Indirect Call Analysis with Large Language Models
Abstract
In contemporary software development, the widespread use of indirect calls to achieve dynamic features poses challenges in constructing precise control flow graphs (CFGs), which further impacts the performance of downstream static analysis tasks. To tackle this issue, various types of indirect call analyzers have been proposed. However, they do not fully leverage the semantic information of the program, limiting their effectiveness in real-world scenarios.
BibTeX
@inproceedings{Cheng-al:ASE24,
author = {Baijun Cheng and
Cen Zhang and
Kailong Wang and
Ling Shi and
Yang Liu and
Haoyu Wang and
Yao Guo and
Ding Li and
Xiangqun Chen},
title = {{Semantic-Enhanced} Indirect Call Analysis with Large Language Models},
booktitle = {ASE},
pages = {430--442},
publisher = {{ACM}},
year = {2024},
}