Fiorella Zampetti

Fiorella Zampetti is a researcher at the University of Sannio, Italy, specializing in empirical software engineering with a focus on continuous integration and delivery, static analysis tools, mining software repositories, and software maintenance and evolution. Her work bridges theoretical research with practical applications in real-world software development environments.

Her research interests span multiple critical areas of modern software engineering, with particular emphasis on

• Experimental methodologies for evaluating software engineering practices
• Technical debt identification and management, especially in emerging domains like deep learning systems
• Continuous integration and delivery pipelines, including common anti-patterns and solutions
• Mining software repositories to extract valuable insights about development processes
• Software quality assessment through static analysis and empirical studies

Analysis of her recent publications reveals an evolving research trajectory that has increasingly incorporated artificial intelligence and large language models into traditional software engineering concerns. Her 2023-2025 work shows a significant focus on how AI-generated code impacts software development practices, licensing concerns, and educational contexts. She has also maintained a strong thread of research on technical debt, particularly examining self-admitted technical debt across different software domains.

Dr. Zampetti has been actively involved in the software engineering research community as a program committee member for major conferences including ASE, ICSE, ESEC/FSE, and ICSME. Her service on these committees demonstrates recognition by her peers as a subject matter expert in her research domains.

Her research has practical implications for software development teams looking to improve their CI/CD practices, manage technical debt effectively, and understand the emerging challenges posed by AI-assisted development tools. She has conducted numerous empirical studies that provide evidence-based insights into software engineering practices across both open-source and industrial contexts.