110 citations · 253 across the 15 of their papers we have counts for
15 papers
LLMs for Automated Unit Test Generation and Assessment in Java: The AgoneTest Framework
Andrea Lops, Fedelucio Narducci, Azzurra Ragone +2
Unit testing is an essential but resource-intensive step in software development, ensuring individual code units function correctly. This paper introduces AgoneTest, an automated e…
Exploring the Use of LLMs for Requirements Specification in an IT Consulting Company
Liliana Pasquale, Azzurra Ragone, Emanuele Piemontese +1
In practice, requirements specification remains a critical challenge. The knowledge necessary to generate a specification can often be fragmented across diverse sources (e.g., meet…
A System for Automated Unit Test Generation Using Large Language Models and Assessment of Generated Test Suites
Andrea Lops, Fedelucio Narducci, Azzurra Ragone +2
Unit tests represent the most basic level of testing within the software testing lifecycle and are crucial to ensuring software correctness. Designing and creating unit tests is a…
Trustworthy AI in practice: an analysis of practitioners' needs and challenges
Maria Teresa Baldassarre, Domenico Gigante, Marcos Kalinowski +2
Recently, there has been growing attention on behalf of both academic and practice communities towards the ability of Artificial Intelligence (AI) systems to operate responsibly an…
The Social Impact of Generative AI: An Analysis on ChatGPT
Maria T. Baldassarre, Danilo Caivano, Berenice Fernandez Nieto +2
In recent months, the social impact of Artificial Intelligence (AI) has gained considerable public interest, driven by the emergence of Generative AI models, ChatGPT in particular.…
POLARIS: A framework to guide the development of Trustworthy AI systems
Maria Teresa Baldassarre, Domenico Gigante, Marcos Kalinowski +1
In the ever-expanding landscape of Artificial Intelligence (AI), where innovation thrives and new products and services are continuously being delivered, ensuring that AI systems a…
A Rapid Review of Responsible AI frameworks: How to guide the development of ethical AI
Vita Santa Barletta, Danilo Caivano, Domenico Gigante +1
In the last years, the raise of Artificial Intelligence (AI), and its pervasiveness in our lives, has sparked a flourishing debate about the ethical principles that should lead its…
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning
Giandomenico Cornacchia, Vito Walter Anelli, Fedelucio Narducci +2
The increasing application of Artificial Intelligence and Machine Learning models poses potential risks of unfair behavior and, in light of recent regulations, has attracted the at…
Counterfactual Reasoning for Bias Evaluation and Detection in a Fairness under Unawareness setting
Giandomenico Cornacchia, Vito Walter Anelli, Fedelucio Narducci +2
Current AI regulations require discarding sensitive features (e.g., gender, race, religion) in the algorithm's decision-making process to prevent unfair outcomes. However, even wit…
How to make latent factors interpretable by feeding Factorization machines with knowledge graphs
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2
Model-based approaches to recommendation can recommend items with a very high level of accuracy. Unfortunately, even when the model embeds content-based information, if we move to…
On the discriminative power of Hyper-parameters in Cross-Validation and how to choose them
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2
Hyper-parameters tuning is a crucial task to make a model perform at its best. However, despite the well-established methodologies, some aspects of the tuning remain unexplored. As…
Knowledge-aware Autoencoders for Explainable Recommender Sytems
Vito Bellini, Angelo Schiavone, Tommaso Di Noia +2
Recommender Systems have been widely used to help users in finding what they are looking for thus tackling the information overload problem. After several years of research and ind…
Computing recommendations via a Knowledge Graph-aware Autoencoder
Vito Bellini, Angelo Schiavone, Tommaso Di Noia +2
In the last years, deep learning has shown to be a game-changing technology in artificial intelligence thanks to the numerous successes it reached in diverse application fields. Am…
The importance of being dissimilar in Recommendation
Vito Walter Anelli, Joseph Trotta, Tommaso Di Noia +2
Similarity measures play a fundamental role in memory-based nearest neighbors approaches. They recommend items to a user based on the similarity of either items or users in a neigh…
Local Popularity and Time in top-N Recommendation
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2
Items popularity is a strong signal in recommendation algorithms. It strongly affects collaborative filtering approaches and it has been proven to be a very good baseline in terms…