Understanding And Managing Non-functional Requirements For Machine Learning Systems

This research project focuses on addressing and managing Non-Functional Requirements (NFRs) for Machine Learning (ML) systems. Through interviews, survey, and a part of systematic mapping study, the research aims to identify current practices and challenges related to NFRs in an ML context, and to develop solutions to manage NFRs for ML systems. The research is using design science as a base of the research method and is working towards proposing a quality framework as an artifact to identify, define, specify, and manage NFRs for ML systems.