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# ASTNN--A Novel Neural Source Code Representation based on Abstract Syntax Tree
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This repository includes the code and experimental data in our paper titled "A Novel Neural Source Code Representation based on Abstract Syntax Tree" that will be presented at ICSE'2019. It can be used to encode code fragments into supervised vectors for various source code related tasks. We have applied the representation in two common tasks: source code classification and code clone detection. It is also expected to be helpful in more tasks.
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This repository includes the code and experimental data in our paper entitled "A Novel Neural Source Code Representation based on Abstract Syntax Tree" that will be presented at ICSE'2019. It can be used to encode code fragments into supervised vectors for various source code related tasks. We have applied our neural source code representation to two common tasks: source code classification and code clone detection. It is also expected to be helpful in more tasks.
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### Requirements
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+ python 3.6<br>
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+ pytorch 0.3.1<br>
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+ pycparser 2.18<br>
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+ javalang 0.11.0<br>
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+ RAM 16GB or more
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+ GPU with CUDA support is also needed
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+ BATCH_SIZE should be configured based on the GPU memory size
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