papers

Publications (5)

cs.SE2025

Enhancing Semantic Understanding in Pointer Analysis using Large Language Models

Baijun Cheng, Kailong Wang, Ling Shi +4

Pointer analysis has been studied for over four decades. However, existing frameworks continue to suffer from the propagation of incorrect facts. A major limitation stems from thei…

cs.SE2025

SliceLocator: Locating Vulnerable Statements with Graph-based Detectors

Baijun Cheng, Kailong Wang, Cuiyun Gao +5

Vulnerability detection is a crucial component in the software development lifecycle. Existing vulnerability detectors, especially those based on deep learning (DL) models, have ac…

cs.SE2024

Semantic-Enhanced Indirect Call Analysis with Large Language Models

Baijun Cheng, Cen Zhang, Kailong Wang +6

In contemporary software development, the widespread use of indirect calls to achieve dynamic features poses challenges in constructing precise control flow graphs (CFGs), which fu…

cs.SE2025

Boosting Pointer Analysis With LLM-Enhanced Allocation Function Detection

Baijun Cheng, Kailong Wang, Ling Shi +5

Pointer analysis is foundational for many static analysis tasks, yet its effectiveness is often hindered by imprecise modeling of heap allocations, particularly in C/C++ programs w…

cs.CR2024

Beyond Fidelity: Explaining Vulnerability Localization of Learning-based Detectors

Baijun Cheng, Shengming Zhao, Kailong Wang +6

Vulnerability detectors based on deep learning (DL) models have proven their effectiveness in recent years. However, the shroud of opacity surrounding the decision-making process o…