https://github.com/haaleo/bug-prediction

Python package to predict bugs using the complexity of code changes
https://github.com/haaleo/bug-prediction

bug bug-detection bug-prediction bugs change complexity entropy fault fault-detection fault-prediction prediciton

Last synced: 23 days ago
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Python package to predict bugs using the complexity of code changes

• Host: GitHub
• URL: https://github.com/haaleo/bug-prediction
• Owner: HaaLeo
• License: bsd-3-clause
• Created: 2019-05-20T10:56:46.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2021-06-18T21:03:59.000Z (almost 5 years ago)
• Last Synced: 2025-04-07T04:32:44.825Z (12 months ago)
• Topics: bug, bug-detection, bug-prediction, bugs, change, complexity, entropy, fault, fault-detection, fault-prediction, prediciton
• Language: Python
• Size: 395 KB
• Stars: 4
• Watchers: 1
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE.txt

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README

          
# bugprediction

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[![Build Status](https://img.shields.io/travis/HaaLeo/bug-prediction/master.svg?style=flat-square)](https://travis-ci.org/HaaLeo/bug-prediction) [![Codecov](https://img.shields.io/codecov/c/github/HaaLeo/bug-prediction.svg?style=flat-square)](https://codecov.io/gh/HaaLeo/bug-prediction) [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)  

[![Donate](https://img.shields.io/badge/☕️-Buy%20Me%20a%20Coffee-blue.svg?&style=flat-square)](https://www.paypal.me/LeoHanisch/3eur)

## Description

This repository enables you to calculate the history complexity metric Ahmed E. Hassan introduced at the [2009 IEEE 31st International Conference on Software Engineering](https://ieeexplore.ieee.org/document/5070510) in May 2009 (DOI: 10.1109/ICSE.2009.5070510) and use it for the prediction of the amount of bugs.

The implementation was part of the course [Software Qualität](https://campus.tum.de/tumonline/wbLv.wbShowLVDetail?pStpSpNr=950402174) at the Technical University of Munich in summer 2019.  

The training data set was derived from the data set that Marco D'Ambros, Michele Lanza and Romain Robbes used in their paper [An Extensive Comparison of Bug Prediction Approaches](https://ieeexplore.ieee.org/document/5463279). The original data set is available at http://bug.inf.usi.ch/index.php.

## Installation

### From Source

```

git clone git@github.com:HaaLeo/bug-prediction.git

cd bug-prediction

pipenv install

pipenv shell

python -m bugprediction --version

```

## Usage

To print all available options:

```

python -m bugprediction --help

```

Training is currently only possible from source. To do so run the edit the `train.py` to your needs and run it.

### API

In order to use the API you need to bundle and install the package:

```

python setup.py sdist bdist_wheel

pip install dist/bugprediction-0.0.1.tar.gz

```

Then you can use tha API like shown bellow:

```python

from bugprediction import calculate_hcm, predict

history_complexity_metric, _ = calculate_hcm(**kwargs)

prediction_map = predict(hcm_map, **args)

```

## Contribution

If you found a bug or are missing a feature do not hesitate to [file an issue](https://github.com/HaaLeo/bug-prediction/issues/new/choose).  

Pull Requests are welcome!

## Support

When you like this package make sure to [star the repository](https://github.com/HaaLeo/bug-prediction/stargazers). I am always looking for new ideas and feedback.  

In addition, it is possible to [donate via paypal](https://www.paypal.me/LeoHanisch/3eur).