1. Code.zip that contains the codes to replicate some parts of this study:
   a. 1_generate_datasets implements our methodology to generate the datasets.
   b. 2_run_models runs the ML models during the evaluation.
   c. 3_result_replication generates charts presented in the paper from the ML evaluation results.
2. Datasets.zip that contain 2 folders:
   a. original datasets: 1 from NVD Vuldeepecker and 3 extracted from BigVul.
   
   b. POPPLER datasets: train, validation, test sets for each time of observation extracted using our methodology from BigVul dataset for project poppler.
3. Pretrained-models.zip that we generated during our evaluation (3 test results for each time point in the timeline [2009-2018]).
4. Results.zip of our evaluation, the folder ALL contains the overall results and other folders are results by model.

UPDATED version 4
- added a GLOBAL_README.md which contains the 3 stages and how they are connected to each other
- updated LineVul.ipynb: import AdamW from torch.optim instead of transformers
- updated README.md in Code2Vec with the prerequisites of Java to run gradlew for astminer

UPDATED version 5
- updated CodeBert.ipynb: import AdamW from torch.optim instead of transformers

Documentations

1. INSTALL.pdf : how to install the codes
2. README.pdf: readme file
3. REQUIREMENTS.pdf: hardware and software requirements
4. STATUS.pdf : status for artifact submission
5. LICENSE.pdf: the license of this artifact
6. PAPER.pdf: the camera-ready version of the paper