30 citations · 68 across the 5 of their papers we have counts for
6 papers · 1 filter
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…
Pynblint: a Static Analyzer for Python Jupyter Notebooks
Luigi Quaranta, Fabio Calefato, Filippo Lanubile
Jupyter Notebook is the tool of choice of many data scientists in the early stages of ML workflows. The notebook format, however, has been criticized for inducing bad programming p…
Towards Productizing AI/ML Models: An Industry Perspective from Data Scientists
Filippo Lanubile, Fabio Calefato, Luigi Quaranta +3
The transition from AI/ML models to production-ready AI-based systems is a challenge for both data scientists and software engineers. In this paper, we report the results of a work…
A Replication Study on Code Comprehension and Expertise using Lightweight Biometric Sensors
Davide Fucci, Daniela Girardi, Nicole Novielli +2
Code comprehension has been recently investigated from physiological and cognitive perspectives through the use of medical imaging. Floyd et al (i.e., the original study) used fMRI…
EMTk -- The Emotion Mining Toolkit
Fabio Calefato, Filippo Lanubile, Nicole Novielli +1
The Emotion Mining Toolkit (EMTk) is a suite of modules and datasets offering a comprehensive solution for mining sentiment and emotions from technical text contributed by develope…