169 citations · 335 across the 56 of their papers we have counts for
58 papers
Fairness Hazard Analysis for Socio-Technical Processes: A Multiple-Case Study in Bias-sensitive Organisational Settings
Giovanna Broccia, Lucio Lelii, Roberto Cirillo +5
Fairness is increasingly recognised as a first-class requirement in socio-technical processes, where interactions among human actors, software systems, and AI technologies may lead…
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…
How Do Developers Maintain and Evolve Their Agents' Instructions? An Empirical Study
Gianmario Voria, Alfonso Cannavale, Andrea De Lucia +3
Context. Autonomous coding agents are increasingly used in software development, shifting parts of the engineering process to AI assistance. While this automation brings clear bene…
An Empirical Study of Gemini 3 for Detecting Natural Language Test Smells in Manual Test Cases
Keila Lucas, Rohit Gheyi, Márcio Ribeiro +3
Manual testing, in which testers follow natural language instructions to validate system behavior, remains essential for uncovering issues that are difficult to capture with automa…
LLM-Assisted Empirical Software Engineering: Systematic Literature Review and Research Agenda
Victoria Gomes, Delaney Selb, Fabio Palomba +2
Context: Empirical Software Engineering (ESE) faces increasing challenges due to data scale, methodological complexity, and reproducibility concerns. Large Language Models (LLMs) h…
From Pixels to Explanations: Interpretable Diabetic Retinopathy Grading with CNN-Transformer Ensembles, Visual Explainability and Vision-Language Models
Pir Bakhsh Khokhar, Carmine Gravino, Fabio Palomba +2
The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers cannot be easily interpreted in t…
Bias Ahead: Sensitive Prompts as Early Warnings for Fairness in Large Language Models
Gianmario Voria, Martina De Lucia, Alessandra Raia +3
Large Language Models (LLMs) are being increasingly integrated into software systems, offering powerful capabilities but also raising concerns about fairness. Existing fairness ben…
SCOPE: A Dataset of Stereotyped Prompts for Counterfactual Fairness Assessment of LLMs
Alessandra Parziale, Gianmario Voria, Valeria Pontillo +3
Large Language Models (LLMs) now serve as the foundation for a wide range of applications, from conversational assistants to decision support tools, making the issue of fairness in…
Investigating Technical Debt Types, Issues, and Solutions in Serverless Computing
Hasini Sumalee Perera, Zadia Codabux, Fabio Palomba
Serverless computing is a cloud execution model where developers run code, and the server management is handled by the cloud provider. Serverless computing is increasingly gaining…
Green Architectural Tactics in ML-enabled Systems: An LLM-based Repository Mining Study
Vincenzo De Martino, Silverio Martínez-Fernández, Fabio Palomba
Context: The increasing adoption of machine learning (ML) and artificial intelligence (AI) technologies raises growing concerns about their environmental sustainability. Developing…
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…
Tracing Stereotypes in Pre-trained Transformers: From Biased Neurons to Fairer Models
Gianmario Voria, Moses Openja, Foutse Khomh +2
The advent of transformer-based language models has reshaped how AI systems process and generate text. In software engineering (SE), these models now support diverse activities, ac…
Transformer-Based Multi-Modal Temporal Embeddings for Explainable Metabolic Phenotyping in Type 1 Diabetes
Pir Bakhsh Khokhar, Carmine Gravino, Fabio Palomba +2
Type 1 diabetes (T1D) is a highly metabolically heterogeneous disease that cannot be adequately characterized by conventional biomarkers such as glycated hemoglobin (HbA1c). This s…
Once Upon a Team: Investigating Bias in LLM-Driven Software Team Composition and Task Allocation
Alessandra Parziale, Gianmario Voria, Valeria Pontillo +4
LLMs are increasingly used to boost productivity and support software engineering tasks. However, when applied to socially sensitive decisions such as team composition and task all…
A Defect is Being Born: How Close Are We? A Time Sensitive Forecasting Approach
Mikel Robredo, Matteo Esposito, Fabio Palomba +2
Background. Defect prediction has been a highly active topic among researchers in the Empirical Software Engineering field. Previous literature has successfully achieved the most a…
Toward Systematic Counterfactual Fairness Evaluation of Large Language Models: The CAFFE Framework
Alessandra Parziale, Gianmario Voria, Valeria Pontillo +3
Nowadays, Large Language Models (LLMs) are foundational components of modern software systems. As their influence grows, concerns about fairness have become increasingly pressing.…
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…
A First Look at the Lifecycle of DL-Specific Self-Admitted Technical Debt
Gilberto Recupito, Vincenzo De Martino, Dario Di Nucci +1
The rapid adoption of Deep Learning (DL)-enabled systems has revolutionized software development, driving innovation across various domains. However, these systems also introduce u…
What Were You Thinking? An LLM-Driven Large-Scale Study of Refactoring Motivations in Open-Source Projects
Mikel Robredo, Matteo Esposito, Fabio Palomba +2
Context. Code refactoring improves software quality without changing external behavior. Despite its advantages, its benefits are hindered by the considerable cost of time, resource…
A Methodological Framework for LLM-Based Mining of Software Repositories
Vincenzo De Martino, Joel Castaño, Fabio Palomba +2
Large Language Models (LLMs) are increasingly used in software engineering research, offering new opportunities for automating repository mining tasks. However, despite their growi…
Investigating the Performance of Small Language Models in Detecting Test Smells in Manual Test Cases
Keila Lucas, Rohit Gheyi, Márcio Ribeiro +3
Manual testing, in which testers follow natural language instructions to validate system behavior, remains crucial for uncovering issues not easily captured by automation. However,…
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…