Task: Security Patch Identification using RNN model.
Developer: Shu Wang
Date: 2020-08-08
Version: S2020.08.08-V4
Description: patch identification using both commit messages and normalized diff code.
File Structure:
|-- SecurityPatchIdentificationRNN
|-- analysis # task analysis.
|-- data # data storage.
|-- negatives # negative samples.
|-- positives # positive samples.
|-- security_patch # positive samples. (official)
|-- temp # temporary stored variables.
|-- data.npy # raw data. (important)
|-- props.npy # properties of diff code. (important)
|-- msgs.npy # commit messages. (important)
|-- ... # other temporary files. (trivial)
|-- SecurityPatchIdentificationRNN.ipynb # main entrance. (Google Colaboratory)
|-- SecurityPatchIdentificationRNN.py # main entrance. (Local)
Dependencies:
pip install clang == 6.0.0.2
pip install torch == 1.2.0 torchvision == 0.4.0
pip install nltk == 3.3
Usage:
python SecurityPatchIdentificationRNN.py