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Presentation by Dr.Abram Hindle (14/06/2018)

Presentation by Professor Hindle of University of Alberta of Canada, famous for analyzing the naturalness of the program.
Natural Language Models and Deep Learning Models of Source Code are competing but serious roadblocks exist in terms of vocabulary size and applicability to real-world unseen projects. Worse yet, it seems that many cases language models do better than deep learned models even when the vocabulary is restricted. In this talk I will describe the work of Eddie Antonio Santos and Joshua Campbell on fixing syntax errors in a variety of programming languages using a variety of models. Furthermore the extension of treating source code as text is extended into the information retrieval domain.


Mr.Hindle[1] Mr.Hindle[2]

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