https://github.com/veydantkatyal/software-bug-prediction
use ML to predict whether software code is likely to contain bugs using historical metrics like code complexity, revisions, and authorship.
https://github.com/veydantkatyal/software-bug-prediction
bug-prediction machine-learning software-quality
Last synced: 9 months ago
JSON representation
use ML to predict whether software code is likely to contain bugs using historical metrics like code complexity, revisions, and authorship.
- Host: GitHub
- URL: https://github.com/veydantkatyal/software-bug-prediction
- Owner: veydantkatyal
- License: mit
- Created: 2025-04-03T13:47:40.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-13T11:04:35.000Z (about 1 year ago)
- Last Synced: 2025-07-05T16:42:32.873Z (12 months ago)
- Topics: bug-prediction, machine-learning, software-quality
- Language: Jupyter Notebook
- Homepage:
- Size: 1.91 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Software Bug Prediction
Predicting software bugs before they occur can save time, money, and effort in the software development life cycle. This project uses machine learning techniques to predict the likelihood of bugs based on historical code and commit metrics.
## Problem Statement
Software bugs are costly and time-consuming. Early prediction of bugs can help in proactive debugging and testing. This project aims to use machine learning models to predict whether a piece of code or commit is likely to contain a bug based on historical features.
## Tech Stack
- **Language**: Python
- **ML Libraries**: scikit-learn, pandas, numpy, matplotlib, seaborn
- **Modeling**: Logistic Regression, Random Forest, XGBoost
- **Evaluation**: Accuracy, Precision, Recall, F1-Score, ROC AUC
## How to Run
1. Clone the repo:
```bash
git clone https://github.com/veydantkatyal/software-bug-prediction.git
cd software-bug-prediction
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
3. Run the hupyter notebook:
```bash
jupyter notebook bug_prediction_.ipynb.ipynb
```
## License
This project is open-source licensed under [MIT License](https://github.com/veydantkatyal/software-bug-prediction/blob/main/LICENSE).