4 papers
Learning Generalizable Multimodal Representations for Software Vulnerability Detection
Zeming Dong, Yuejun Guo, Qiang Hu +5
Source code and its accompanying comments are complementary yet naturally aligned modalities-code encodes structural logic while comments capture developer intent. However, existin…
An Empirical Study of the Imbalance Issue in Software Vulnerability Detection
Yuejun Guo, Qiang Hu, Qiang Tang +1
Vulnerability detection is crucial to protect software security. Nowadays, deep learning (DL) is the most promising technique to automate this detection task, leveraging its superi…
Boosting Source Code Learning with Text-Oriented Data Augmentation: An Empirical Study
Zeming Dong, Qiang Hu, Yuejun Guo +5
Recent studies have demonstrated remarkable advancements in source code learning, which applies deep neural networks (DNNs) to tackle various software engineering tasks. Similar to…
Evaluation and Improvement of Fault Detection for Large Language Models
Qiang Hu, Jin Wen, Maxime Cordy +4
Large language models (LLMs) have recently achieved significant success across various application domains, garnering substantial attention from different communities. Unfortunatel…