Generation of code from text description with syntactic parsing and Tree2Tree model

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dc.contributor.author Stehnii, Anatolii
dc.date.accessioned 2018-01-25T18:36:11Z
dc.date.available 2018-01-25T18:36:11Z
dc.date.issued 2018
dc.identifier.citation Stehnii, Anatolii. Generation of code from text description with syntactic parsing and Tree2Tree model : Master Thesis : manuscript / Anatolii Stehnii ; Supervisor Dr. Rostyslav Hryniv ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2017. – 67 p. : ill. uk
dc.identifier.uri http://er.ucu.edu.ua/handle/1/1191
dc.description.abstract Software development requires vast knowledge of different programming tools which cannot be kept in human memory. Therefore software developers often formulate their task in human language to query online knowledge bases like StackOverflow to get short snippets of code. In this work, we explored the way of code generation from natural language description and prepared web API for Python which translates NL descriptions to short snippets of code. Our model implements sequence-to-sequence model with recursive encoder and uses syntactic trees instead of plain sequence on input. Results have not outperformed current state-of-the-art performance. However, presented Tree2Tree model has potential in other applications and this work makes a solid base for a further research. uk
dc.language.iso en uk
dc.subject Tree2Tree model uk
dc.subject Abstract syntax tree generation uk
dc.subject Action probabilities uk
dc.title Generation of code from text description with syntactic parsing and Tree2Tree model uk
dc.type Preprint uk
dc.status Опублікований і розповсюджений раніше uk


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