24 citations · 58 across the 21 of their papers we have counts for
7 papers · 1 filter
Testing in the Evolving World of DL Systems:Insights from Python GitHub Projects
Qurban Ali, Oliviero Riganelli, Leonardo Mariani
In the ever-evolving field of Deep Learning (DL), ensuring project quality and reliability remains a crucial challenge. This research investigates testing practices within DL proje…
ReProbe: An Architecture for Reconfigurable and Adaptive Probes
Federico Alessi, Alessandro Tundo, Marco Mobilio +2
Modern distributed systems are highly dynamic and scalable, requiring monitoring solutions that can adapt to rapid changes. Monitoring systems that rely on external probes can only…
Towards Model-Driven Dashboard Generation for Systems-of-Systems
Maria Teresa Rossi, Alessandro Tundo, Leonardo Mariani
Configuring and evolving dashboards in complex and large-scale Systems-of-Systems (SoS) can be an expensive and cumbersome task due to the many Key Performance Indicators (KPIs) th…
Assessing AI-Based Code Assistants in Method Generation Tasks
Vincenzo Corso, Leonardo Mariani, Daniela Micucci +1
AI-based code assistants are increasingly popular as a means to enhance productivity and improve code quality. This study compares four AI-based code assistants, GitHub Copilot, Ta…
Generating Java Methods: An Empirical Assessment of Four AI-Based Code Assistants
Vincenzo Corso, Leonardo Mariani, Daniela Micucci +1
AI-based code assistants are promising tools that can facilitate and speed up code development. They exploit machine learning algorithms and natural language processing to interact…
Analyzing Prompt Influence on Automated Method Generation: An Empirical Study with Copilot
Ionut Daniel Fagadau, Leonardo Mariani, Daniela Micucci +1
Generative AI is changing the way developers interact with software systems, providing services that can produce and deliver new content, crafted to satisfy the actual needs of dev…
Anonymizing Test Data in Android: Does It Hurt?
Elena Masserini, Davide Ginelli, Daniela Micucci +2
Failure data collected from the field (e.g., failure traces, bug reports, and memory dumps) represent an invaluable source of information for developers who need to reproduce and a…