3 citations · 4 across the 4 of their papers we have counts for
4 papers
Contextual Fairness-Aware Practices in ML: A Cost-Effective Empirical Evaluation
Alessandra Parziale, Gianmario Voria, Giammaria Giordano +3
As machine learning (ML) systems become central to critical decision-making, concerns over fairness and potential biases have increased. To address this, the software engineering (…
Data Preparation for Fairness-Performance Trade-Offs: A Practitioner-Friendly Alternative?
Gianmario Voria, Rebecca Di Matteo, Giammaria Giordano +2
As machine learning (ML) systems are increasingly adopted across industries, addressing fairness and bias has become essential. While many solutions focus on ethical challenges in…
When Code Smells Meet ML: On the Lifecycle of ML-specific Code Smells in ML-enabled Systems
Gilberto Recupito, Giammaria Giordano, Filomena Ferrucci +2
Context. The adoption of Machine Learning (ML)--enabled systems is steadily increasing. Nevertheless, there is a shortage of ML-specific quality assurance approaches, possibly beca…
On the Adoption and Effects of Source Code Reuse on Defect Proneness and Maintenance Effort
Giammaria Giordano, Gerardo Festa, Gemma Catolino +3
Context. Software reusability mechanisms, like inheritance and delegation in Object-Oriented programming, are widely recognized as key instruments of software design. These are use…