Challenging Machine Learning-based Clone Detectors via Semantic-preserving Code Transformations

This repository includes the code and experimental data in our paper entitled "Challenging Machine Learning-based Clone Detectors via Semantic-preserving Code Transformations" . It can be used to perform equivalent transformations on code.

requirements

torch=1.9.1

torchvision=0.7.0+cu101

TXL=v10.8 (7.5.20)

GPU with CUDA support is also needed

How to install

Please refer to Torch

git clone https://github.com/CloneGen/CLONEGEN.git

Txl:

tar -zxf 17867-txl10.8a.linux64.tar.gz

cd txl10.8a.linux64/

./InstallTxl

Test Demo, For a simple test,

cd CodeTransformationTest

chmod 755 runner.sh

chmod 755 RM/mutation.sh

# run: ./runner.sh  testfile.c  action
./runner.sh motivation.c 1
./runner.sh motivation.c 2
...
./runner.sh motivation.c 7

Note: Only a simple test version is provided here, other codes will be made public once the paper has been accepted.

Dataset

CloneGen.tar.gz is the data corresponding to the four strategies in the paper.

Here are the parts that are not yet open source.

Usage.

1. Code Transformation(heuristics method)

cd HeuristicsMethod
./runner.sh test.c RS
./runner.sh test.c GA
./runner.sh test.c MCMC

2. Code Clone Detection

cd TextLSTM
./prepare.sh

3. DRLSG Transformation

cd DRLSG

# Training
python drlsg_main.py --mode train --rlmodel_path ./saved_dict/ppo_chekpoint.zip --project_path /home/zww/rlcone_release/DRLSG --code_path ./test.c --vocab_path ./vocab.json

# Testing
python drlsg_main.py --mode test --rlmodel_path ./saved_dict/ppo_chekpoint.zip --project_path /home/zww/rlcone_release/DRLSG/ --code_path ./test.c --vocab_path ./vocab.json

The results are stored in CloneRM/Mutated.c.