5 papers
Robust Smart Contract Vulnerability Detection via Contrastive Learning-Enhanced Granular-ball Training
Zeli Wang, Qingxuan Yang, Shuyin Xia +3
Deep neural networks (DNNs) have emerged as a prominent approach for detecting smart contract vulnerabilities, driven by the growing contract datasets and advanced deep learning te…
JC-Finder: Detecting Java Clone-based Third-Party Library by Class-level Tree Analysis
Lida Zhao, Chaofan Li, Yueming Wu +10
While reusing third-party libraries (TPL) facilitates software development, its chaotic management has brought great threats to software maintenance and the unauthorized use of sou…
Detecting Essence Code Clones via Information Theoretic Analysis
Lida Zhao, Shihan Dou, Yutao Hu +8
Code cloning, a widespread practice in software development, involves replicating code fragments to save time but often at the expense of software maintainability and quality. In t…
TGMM: Combining Parse Tree with GPU for Scalable Multilingual and Multi-Granularity Code Clone Detection
Yuhang Ye, Yuekun Wang, Yinxing Xue +2
The rapid evolution of programming languages and software systems has necessitated the implementation of multilingual and scalable clone detection tools. However, it is difficult t…
An Empirical Study of Vulnerability Detection using Federated Learning
Peiheng Zhou, Ming Hu, Xingrun Quan +6
Although Deep Learning (DL) methods becoming increasingly popular in vulnerability detection, their performance is seriously limited by insufficient training data. This is mainly b…