This project is Python implementation of a work by Caliskan et al. for Java language.
Clone the repo and install python packages:
git clone https://github.com/rebryk/code_stylometry.git
cd code_stylometry
pip install -r requirements.txt
Training and validation data is represented by source code of solutions to programming tasks from the international programming competition Google Code Jam.
data/metadata.json contains description of rounds and problems that were used to create the dataset.
If you want to download the corpus on your machine, run the following code:
cd data/
python crawler.py
It will download the solution files in java into data/codejam directory.
File paths will look like data/codejam/<round_id>/<problem_id>/<username>.java
The features package contains a few useful functions:
calculate_features_for_files(files)
This function calculates sets of features for the given source files.
Usage example:samples = calculate_features_for_files(['A.java', B.java'])build_dataset(samples)
Builds a pandas data frame from the given list of feature sets.
Usage example:df = build_dataset(samples)
You can open De-anonymizing Programmers via Code Stylometry.ipynb to see how the methods above are used to de-anonymize 100 users with 9 code files each.
CatBoost is used to train the model.