Deep Learning & Software Engineering: State of Research and Future Directions

Prem Devanbu; Matthew Dwyer; Sebastian Elbaum; Michael Lowry; Kevin Moran; Denys Poshyvanyk; Baishakhi Ray; Rishabh Singh; Xiangyu Zhang

arXiv · 2009.08525

Deep Learning & Software Engineering: State of Research and Future Directions

Prem Devanbu·Matthew Dwyer·Sebastian Elbaum·Michael Lowry·Kevin Moran·Denys Poshyvanyk·Baishakhi Ray·Rishabh Singh·Xiangyu Zhang

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Abstract

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.

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BibTeX RIS

Prem Devanbu, Matthew Dwyer, Sebastian Elbaum, Michael Lowry, Kevin Moran, Denys Poshyvanyk, Baishakhi Ray, Rishabh Singh, Xiangyu Zhang. 2020-09-17. Deep Learning & Software Engineering: State of Research and Future Directions. https://arxiv.org/abs/2009.08525

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