9 papers
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…
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…
Socio-Technical Well-Being of Quantum Software Communities: An Overview on Community Smells
Stefano Lambiase, Manuel De Stefano, Fabio Palomba +2
Quantum computing has gained significant attention due to its potential to solve computational problems beyond the capabilities of classical computers. With major corporations and…
Sustainability of Machine Learning-Enabled Systems: The Machine Learning Practitioner's Perspective
Vincenzo De Martino, Stefano Lambiase, Fabiano Pecorelli +3
Software sustainability is a key multifaceted non-functional requirement that encompasses environmental, social, and economic concerns, yet its integration into the development of…
How Do Communities of ML-Enabled Systems Smell? A Cross-Sectional Study on the Prevalence of Community Smells
Giusy Annunziata, Stefano Lambiase, Fabio Palomba +2
Effective software development relies on managing both collaboration and technology, but sociotechnical challenges can harm team dynamics and increase technical debt. Although team…
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…