Abstract Machine learning techniques, especially deep learning, have achieved remarkable
breakthroughs over the past decade. At present, machine learning applications are …

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 …

The introduction of machine learning (ML) components in software projects has created the
need for software engineers to collaborate with data scientists and other specialists. While …

Significant interest in applying Deep Neural Network (DNN) has fueled the need to support
engineering of software that uses DNNs. Repairing software that uses DNNs is one such …

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

Bindings for machine learning frameworks (such as TensorFlow and PyTorch) allow
developers to integrate a framework's functionality using a programming language different …

In recent years, studies on the user experience have emerged as an indispensable part of
any gamification research. The study of user experience enables gamification designers and …

Data scientists reportedly spend a significant amount of their time in their daily routines on
data wrangling, ie cleaning data and extracting features. However, data wrangling code is …

Machine Learning (ML) is being used in multiple disciplines due to its powerful capability to
infer relationships within data. In particular, Software Engineering (SE) is one of those …

Partial code execution is the problem of executing code with missing definitions. The
problem has gained recent traction as solutions to the problem could enable various …