  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.

Software Engineering;Artificial Intelligence;Machine Learning