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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.
Abstract:
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.

Pictures

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

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