Programming with "Big Code": Lessons, Techniques and Applications

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A Survey of Machine Learning for Big Code and Naturalness (2017, background): “ted Reviews and other Resources. There have been short reviews summarizing the progress and the vision of the research area, from both software engineering [52] and programming languages perspectives [28, 195]. However, none of these articles can be considered extensive literature reviews, which is ”
Bayesian specification learning for finding API usage errors (2017, background): “The availability of large corpora of open-source code makes this idea especially appealing [15].”
GaDei: On Scale-Up Training as a Service for Deep Learning (2016, background): “ relatively large communication overhead due to intermediate data copy. Our solution solves these issues by min12 2019/4/5 imizing the data copy and making the whole system highly concurrent. Big code[10, 43] is an emerging research area, where researchers apply machine learning , and especially dee”