Artificial Intelligence (AI) in medical applications holds great promise. However, the use of
Machine Learning-based (ML) systems in clinical practice is still minimal. It is uniquely …

Code intelligence leverages machine learning techniques to extract knowledge from
extensive code corpora, with the aim of develo** intelligent tools to improve the quality …

As software vulnerabilities grow in volume and complexity, researchers proposed various
Artificial Intelligence (AI)-based approaches to help under-resourced security analysts to …

Memory-related vulnerabilities constitute severe threats to the security of modern software.
Despite the success of deep learning-based approaches to generic vulnerability detection …

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 increase in software vulnerabilities that cause significant economic and social
losses, automatic vulnerability detection has become essential in software development and …

In software development, it is critical to detect vulnerabilities in a project as early as possible.
Although, deep learning has shown promise in this task, current state-of-the-art methods …

Code completion, a highly valuable topic in the software development domain, has been
increasingly promoted for use by recent advances in large language models (LLMs). To …

In the software engineering (SE) community, deep learning (DL) has recently been applied
to many source code processing tasks, achieving state-of-the-art results. Due to the poor …

JavaScript (JS) is a popular, platform-independent programming language. To ensure the
interoperability of JS programs across different platforms, the implementation of a JS engine …