Towards a Grounded Theory for a Development Process Model for Machine Learning Based Systems

Abstract

The software industry has experienced the integration of artificial intelligence capabilities into applications, facing new challenges regarding software development. Despite research and industry contributions providing lessons learned and best practices, no study proposed a reference process for developing this type of software, and practitioners still struggle to establish a working process. Through a Grounded Theory study involving practitioners with experience in machine learning (ML) projects, this paper presents an emerging theory of how ML-based systems are developed. The reported results comprise key elements of a reference development process with its respective phases and activities.