Masters Thesis
A Deep Dive Into Automatic Code Generation Using Character Based Recurrent Neural Networks
Deep Learning is an emerging field in Artificial Intelligence that uses biologically inspired neural networks to recognize patterns in the natural world. These neural networks have an amazing ability to process large amounts of data and learn from them. Recurrent Neural Networks (RNN) are used in applications involving natural language processing like text translations and text generation. This research evaluates the effectiveness of a RNN to be able to automatically generate programming code. Programming languages are different from natural languages in that they have unique structure and syntax. The goal for this research is to conduct experiments on a character RNN model with for three programming languages; Java, Python and C#, and evaluate the results by testing and analyzing the ability for the RNN to automatically produce code that is able to compile.
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PriyaRenita_Thesis2017.pdf | 2020-07-12 | Public | Download |
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