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Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree

Code for paper "Detecting Code Clones with Graph Neural Network and Flow-Augmented Abstract Syntax Tree", SANER 2020

Requires:

pytorch    
javalang  
pytorch-geometric  

Data

  • Google Code Jam snippets in googlejam4_src.zip
  • Google Code Jam clone pairs in javadata.zip
  • BigCloneBench snippets and clone pairs in BCB.zip

Running

  • Run experiments on Google Code Jam: python run_java.py
  • For BigCloneBench: python run_bcb.py

This operation include training, validation, testing and writing test results to files.

Arguments:

  • nextsib, ifedge, whileedge, foredge, blockedge, nexttoken, nextuse: whether to include these edge types in FA-AST
  • data_setting: whether to perform data balance on training set
    '0': no data balance
    '11': pos:neg = 1:1
    '13': pos:neg = 1:3
    '0'/'11'/'13'/+'small': use a smaller version of the training set

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