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

The gaming industry is an important part of today’s economy. Statistically, many quality issues are found by users in released products or updates. One reason for this is that testing methods from general software development cannot be transferred to test visual outputs without significant human effort. This work focuses on a major problem in this area, namely testing the correctness of the images displayed by cameras in relation to the content of the environment they are intended to see. The techniques used are a combination of state-of-the-art computer vision methods adapted to our specific use cases. Evaluation is performed in a well-known soccer game engine and shows that the proposed methods have the potential to significantly reduce manual work and development costs while improving product quality.

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