How do engineers perceive difficulties in engineering of machine-learning systems?: questionnaire survey

There is increasing interest in machine learning (ML) techniques and their applications in recent years. Although there has been intensive support by frameworks and libraries for the implementation of ML-based systems, investigation into engineering disciplines and methods is still at the early phase. The most pressing issue in this field is identifying the essential challenges for the software engineering research community as engineering of ML-based systems requires novel approaches due to the essentially different nature of ML-based systems. In this paper, we analyze the results of a questionnaire administered to 278 people who have worked on ML-based systems in practice, clarify the essential difficulties and their causes as perceived by practitioners, and suggest potential research directions.