1 citations · 1 across the 4 of their papers we have counts for
5 papers
LLM-Enhanced Hierarchical Heterogeneous Graph Representation Learning for Malicious Python Package Detection
Hang Gao, Xiaoyu Chen, Baoquan Cui +4
Malicious Python packages have become a major threat to software supply chain ecosystems due to the widespread adoption of open-source repositories such as PyPI. Existing learning-…
Efficient Code Analysis via Graph Representation Learning-Guided Large Language Models
Hang Gao, Tao Peng, Baoquan Cui +4
Large Language Models (LLMs) have significantly advanced code analysis tasks, yet they struggle to detect malicious behaviors fragmented across files, whose intricate dependencies…
An Empirical Study: MEMS as a Static Performance Metric
Liwei Zhang, Baoquan Cui, Xutong Ma +1
Static performance estimation is essential during compile-time analysis, yet traditional runtime-based methods are costly and platform-dependent. We investigate mems, the number of…
JustinANN: Realistic Test Generation for Java Programs Driven by Annotations
Baoquan Cui, Rong Qu, Jian Zhang
Automated test case generation is important. However, the automatically generated test input does not always make sense, and the automated assertion is difficult to validate agains…
Improving Tese Case Generation for Python Native Libraries Through Constraints on Input Data Structures
Xin Zhang, Xutong Ma, Jiwen Yan +3
Modern Python projects execute computational functions using native libraries and give Python interfaces to boost execution speed; hence, testing these libraries becomes critical t…