Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

Actionable Warning Identification (AWI) plays a crucial role in improving the usability of static
code analyzers. With recent advances in Machine Learning (ML), various approaches have …

Large language models for code (LLM4Code), which demonstrate strong performance (eg,
high accuracy) in processing source code, have significantly transformed software …

Despite decades of research in vulnerability detection, vulnerabilities in source code remain
a growing problem, and more effective techniques are needed in this domain. To enhance …

Large Language models have achieved impressive performance in automated software
engineering. Extensive efforts have been made to evaluate the abilities of code LLMs in …

Large Language Models (LLMs) have become instrumental in advancing software
engineering (SE) tasks, showcasing their efficacy in code understanding and beyond. AI …

The rapid expansion of software systems and the growing number of reported vulnerabilities
have emphasized the importance of accurately identifying vulnerable code segments …

Large Language Models for Code (code LLMs) have demonstrated remarkable performance
across various software engineering (SE) tasks, increasing the application of code LLMs in …

Leveraging deep learning (DL)-based code analysis tools to solve software engineering
tasks is becoming increasingly popular. Code models often suffer performance degradation …

Large Language Models (LLMs) have garnered remarkable advancements across diverse
code-related tasks, known as Code LLMs, particularly in code generation that generates …