61 citations · 181 across the 12 of their papers we have counts for
12 papers
A Multivocal Literature Review on the Benefits and Limitations of Automated Machine Learning Tools
Kelly Azevedo, Luigi Quaranta, Fabio Calefato +1
Context. Advancements in Machine Learning (ML) are revolutionizing every application domain, driving unprecedented transformations and fostering innovation. However, despite these…
Assessing the Use of AutoML for Data-Driven Software Engineering
Fabio Calefato, Luigi Quaranta, Filippo Lanubile +1
Background. Due to the widespread adoption of Artificial Intelligence (AI) and Machine Learning (ML) for building software applications, companies are struggling to recruit employe…
A Lot of Talk and a Badge: An Exploratory Analysis of Personal Achievements in GitHub
Fabio Calefato, Luigi Quaranta, Filippo Lanubile
Context. GitHub has introduced a new gamification element through personal achievements, whereby badges are unlocked and displayed on developers' personal profile pages in recognit…
Teaching MLOps in Higher Education through Project-Based Learning
Filippo Lanubile, Silverio Martínez-Fernández, Luigi Quaranta
Building and maintaining production-grade ML-enabled components is a complex endeavor that goes beyond the current approach of academic education, focused on the optimization of ML…
A Preliminary Investigation of MLOps Practices in GitHub
Fabio Calefato, Filippo Lanubile, Luigi Quaranta
Background. The rapid and growing popularity of machine learning (ML) applications has led to an increasing interest in MLOps, that is, the practice of continuous integration and d…
Assessing the Quality of Computational Notebooks for a Frictionless Transition from Exploration to Production
Luigi Quaranta
The massive trend of integrating data-driven AI capabilities into traditional software systems is rising new intriguing challenges. One of such challenges is achieving a smooth tra…