Deep Learning & Software Engineering: State of Research and Future Directions
It outlines directions for researchers in software engineering and AI, but is incremental as it synthesizes existing discussions without new results.
This paper summarizes a workshop that identified high-priority research areas at the intersection of deep learning and software engineering, aiming to provide a roadmap for future work.
Given the current transformative potential of research that sits at the intersection of Deep Learning (DL) and Software Engineering (SE), an NSF-sponsored community workshop was conducted in co-location with the 34th IEEE/ACM International Conference on Automated Software Engineering (ASE'19) in San Diego, California. The goal of this workshop was to outline high priority areas for cross-cutting research. While a multitude of exciting directions for future work were identified, this report provides a general summary of the research areas representing the areas of highest priority which were discussed at the workshop. The intent of this report is to serve as a potential roadmap to guide future work that sits at the intersection of SE & DL.