The increasing essential complexity of software systems makes current software
engineering methods and practices fall short in many occasions. Software assistants have …

Data scientists often develop machine learning models to solve a variety of problems in the
industry and academy but not without facing several challenges in terms of Model …

The application of machine learning (ML) algorithms to address problems related to model-
driven engineering (MDE) is currently hindered by the lack of curated datasets of software …

Metamorphic testing is a well-established testing technique that has been successfully
applied in various domains, including testing deep learning models to assess their …

Recently, there has been a significant increase in the number of Artificial Intelligence (AI)
systems, software, and components. As a result, it is crucial to evaluate their quality. Quality …

In model-driven software engineering, models are used in all phases of the development
process. These models must hold a high quality since the implementation of the systems …

Artificial intelligence has already proven to be a powerful tool to automate and improve how
we deal with software development processes. The application of artificial intelligence to …

The increasing integration of AI software into various aspects of our daily lives has amplified
the importance of evaluating the quality of these intelligent systems. The rapid proliferation …

Deep predictive models have been widely employed in software engineering (SE) tasks due
to their remarkable success in artificial intelligence (AI). Most of these models are trained in …

Machine Learning (ML) can substantially improve the efficiency and effectiveness of
organizations and is widely used for different purposes within Software Engineering …