Deep Learning & Software Engineering: State of Research and Future Directions
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.
- Publication:
-
arXiv e-prints
- Pub Date:
- September 2020
- DOI:
- 10.48550/arXiv.2009.08525
- arXiv:
- arXiv:2009.08525
- Bibcode:
- 2020arXiv200908525D
- Keywords:
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- Computer Science - Software Engineering;
- Computer Science - Artificial Intelligence;
- Computer Science - Machine Learning
- E-Print:
- Community Report from the 2019 NSF Workshop on Deep Learning &