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 …

Machine learning (ML) is used increasingly in real-world applications. In this paper, we
describe our ongoing endeavor to define characteristics and challenges unique to …

Background. The increasing reliance on applications with machine learning (ML)
components calls for mature engineering techniques that ensure these are built in a robust …

Internet of Things (IoT) communication technologies have brought immense revolutions in
various domains, especially in health monitoring systems. Machine learning techniques …

Abstract Context: Engineering Artificial Intelligence (AI) software is a relatively new area with
many challenges, unknowns, and limited proven best practices. Big companies such as …

In traditional approaches to building software systems (that do not include an Artificial
Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) …

With the emergence of Blockchain-based Internet of Things (BIoT) applications, smart
contracts have become one of the most appealing aspects because they reduce the cost …

Selenium is often considered the de-facto standard framework for end-to-end web testing
nowadays. It allows practitioners to drive web browsers (such as Chrome, Firefox, Edge, or …