EASE 2024
Tue 18 - Fri 21 June 2024 Salerno, Italy

The recent expansion of photovoltaic (PV) systems and increased production scale necessitate enhanced monitoring to assess system performance, detect potential degradation, and identify imminent failures, ensuring sustained quality and optimal performance throughout their lifecycle. However, the requirement for sophisticated and costly monitoring systems generally restricts their use to larger-scale residential and commercial sectors. The TERRASOS Project (POR CAMPANIA FESR 2014/2020) addressed these challenges through deep investigation and field experiments. MEDIACOM SRL developed a performance prediction system that minimizes parameters’ count, simplifies hardware requirements, reduces transmission bandwidth, and shortens processing times. Obtained results are promising, and enable a broader and costeffective adoption of PV systems.

Thu 20 Jun

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

14:00 - 15:25
Artificial Intelligence for Software EngineeringIndustry / Research Papers / Short Papers, Vision and Emerging Results at Room Capri
Chair(s): Sridhar Chimalakonda Indian Institute of Technology, Tirupati, Klaus Schmid University of Hildesheim
14:00
15m
Talk
A Performance Study of LLM-Generated Code on Leetcode
Research Papers
Tristan Coignion , Clement Quinton University of Lille, Inria, Romain Rouvoy Univ. Lille / Inria / CNRS
Pre-print
14:15
15m
Talk
How Much Logs Does My Source Code File Need? Learning to Predict the Density of Logs
Research Papers
Mohamed Amine Batoun École de Technologie Supérieure, Mohammed Sayagh ETS Montreal, University of Quebec, Ali Ouni ETS Montreal, University of Quebec
14:30
15m
Talk
The Promise and Challenges of using LLMs to Accelerate the Screening Process of Systematic Reviews
Research Papers
Aleksi Huotala University of Helsinki, Miikka Kuutila Dalhousie University, Paul Ralph Dalhousie University, Mika Mäntylä University of Helsinki and University of Oulu
Link to publication DOI Pre-print
14:45
15m
Talk
AI-enabled efficient PVM performance monitoring
Industry
Mario Veniero Independent Researcher, Davide Varriale MEDIACOM SRL
DOI
15:00
15m
Talk
Automated evaluation of game content display using deep learning
Industry
Ciprian Paduraru University of Bucharest, Marina Cernat University of Bucharest, Alin Stefanescu University of Bucharest
15:15
10m
Talk
Automated categorization of pre-trained models in software engineering: A case study with a Hugging Face dataset
Short Papers, Vision and Emerging Results
Claudio Di Sipio University of L'Aquila, Riccardo Rubei University of L'Aquila, Juri Di Rocco University of L'Aquila, Davide Di Ruscio University of L'Aquila, Phuong T. Nguyen University of L’Aquila
Pre-print