论文标题

深度学习与软件工程:研究和未来方向

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

论文作者

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

论文摘要

鉴于目前位于深度学习(DL)与软件工程(SE)的交集的研究潜力,NSF赞助的社区研讨会是与在加利福尼亚州圣地亚哥举行的第34 IEEE/ACM国际自动软件工程(ASE'19)共同开展的。该研讨会的目的是概述横切研究的高优先级领域。尽管确定了许多令人兴奋的方向,但该报告提供了代表优先领域的研究领域的一般摘要,这些研究领域在研讨会上进行了讨论。该报告的目的是作为指导SE&DL交汇处的未来工作的潜在路线图。

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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