Software vulnerabilities have always been an essential issue in cyberspace, for which many
vulnerability detection techniques have been investigated. Among them, deep learning …

Recently, deep learning techniques have garnered substantial attention for their ability to
identify vulnerable code patterns accurately. However, current state-of-the-art deep learning …

Due to multitudinous vulnerabilities in sophisticated software programs, the detection
performance of existing approaches requires further improvement. Multiple vulnerability …

Recently, deep learning techniques have garnered substantial attention for their ability to
identify vulnerable code patterns accurately. However, current state-of-the-art deep learning …

Traditional vulnerability detection mostly ran on rules or source code similarity with manually
defined vulnerability features. In fact, these vulnerability rules or features are difficult to be …

Vulnerability detection is essential to protect software systems. Various approaches based
on deep learning have been proposed to learn the pattern of vulnerabilities and identify …

The automatic vulnerability detection on program source code is an important research
topic. With the development of artificial intelligence, deep learning has been applied to …

In order to secure software, it is critical to detect potential vulnerabilities. The performance of
traditional static vulnerability detection methods is limited by predefined rules, which rely …

With the flourishing of the open‐source software community, the problem of software
vulnerabilities is becoming more and more serious. Hence, it is urgent to come up with an …

Context: Previous studies have shown that existing deep learning-based approaches can
significantly improve the performance of vulnerability detection. They represent code in …