11 papers
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…
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…
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…
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…
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.…