Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

Context: In traditional software systems, Requirements Engineering (RE) activities are well-
established and researched. However, building Artificial Intelligence (AI) based software …

AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …

Abstract The Internet of Things (IoT) technology with wearable devices provides a promising
solution that enables con-tinuous monitoring of health parameters. Non-invasive sensors …

The explorative and iterative nature of developing and operating ML applications leads to a
variety of artifacts, such as datasets, features, models, hyperparameters, metrics, software …

Nowadays, systems containing components based on machine learning (ML) methods are
becoming more widespread. In order to ensure the intended behavior of a software system …

Machine Learning (ML) is an application of Artificial Intelligence (AI) that uses big data to
produce complex predictions and decision-making systems, which would be challenging to …

In the last few years, artificial intelligence (AI) and machine learning (ML) have become
ubiquitous terms. These powerful techniques have escaped obscurity in academic …

Machine learning (ML) has become a core feature for today's real-world applications,
making it a trending topic for the software engineering community. Requirements …

Both conceptual modeling and machine learning have long been recognized as important
areas of research. With the increasing emphasis on digitizing and processing large amounts …