3 papers
cs.SE2026
TARS: A Theory-of-Mind Agent for Personalized In-IDE Code Comprehension
Leopoldo Todisco, Antonio Della Porta, Stefano Lambiase +1
Code comprehension is one of the most time-consuming tasks in software engineering, yet most LLM-based assistants produce explanations that ignore who is asking and force developer…
cs.CR2026
The Language of Security: How Prompt Syntax Shapes Secure Code Generation in Open LLMs
Matteo Cicalese, Antonio Della Porta, Stefano Lambiase +4
Large Language Models (LLMs) are increasingly used for source code generation despite their outputs often exhibiting security vulnerabilities. Prior work shows that prompt engineer…
cs.SE2025
Do Prompt Patterns Affect Code Quality? A First Empirical Assessment of ChatGPT-Generated Code
Antonio Della Porta, Stefano Lambiase, Fabio Palomba
Large Language Models (LLMs) have rapidly transformed software development, especially in code generation. However, their inconsistent performance, prone to hallucinations and qual…