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Code for paper, "Pathways to Leverage Transcompiler based Data Augmentation for Cross-Language Clone Detection", ICPC 2023

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clone_transcompiler

Code for paper, "Pathways to Leverage Transcompiler based Data Augmentation for Cross-Language Clone Detection", ICPC 2023

Installation

To set up the project, follow these steps:

  1. Install dependencies by executing the following scripts:
    • install_server.sh
    • srcml_dep.sh
    • requirements.txt

Model Training and Testing

To train or test the models, it is recommended to use a virtual environment. Follow the specific requirements outlined in the requirements.txt file. For additional model-specific instructions, refer to the repository of the target model.

Setting up ANTLR and Transcoder

Detailed instructions for setting up ANTLR and Transcoder can be found in the following files:

  • setup_antlr.txt
  • setup_transcoder.txt

Clone Pairs and Dataset Generation

To generate clone pairs and datasets, follow these steps:

  • Run the provided notebooks sequentially, ensuring dependencies are met
  • Feature extraction using ANTLR (find in CLCDSA repo)
  • Utilize the clone pairs generation method provided in the CLCDSA repo (requires Java)

For more information, refer to the respective repositories and documentation.

Required Models and Other Repositories

Contact

Subroto Nag Pinku, subroto.npi@usask.ca

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Code for paper, "Pathways to Leverage Transcompiler based Data Augmentation for Cross-Language Clone Detection", ICPC 2023

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