manishkk / bugbug

Platform for Bugzilla Machine Learning projects

bugbug

Contributing

1. Issues marked as good first issue are self-contained enough that a contributor should be able to work on them.
2. Issues marked as reserved-for-beginners are reserved for people who have never contributed to the project before.
3. Issues are to be considered as not assigned, until there is a PR linked to them.

Classifiers

• bug vs feature - Bugs on Bugzilla aren't always bugs. Sometimes they are feature requests, refactorings, and so on. The aim of this classifier is to distinguish between bugs that are actually bugs and bugs that aren't. The dataset currently contains 2110 bugs, the accuracy of the current classifier is ~93% (precision ~95%, recall ~94%).

• regression vs non-regression - Bugzilla has a regression keyword to identify bugs that are regressions. Unfortunately it isn't used consistently. The aim of this classifier is to detect bugs that are regressions.

• tracking - The aim of this classifier is to detect bugs to track.

• uplift - The aim of this classifier is to detect bugs for which uplift should be approved and bugs for which uplift should not be approved.

Setup

Run pip install -r requirements.txt and pip install -r test-requirements.txt

If you update the bugs database, run xz -v9 -k data/bugs.json. If you update the commits database, run xz -v9 -k data/commits.json.

Usage

Run the run.py script to perform training / classification. The first time run.py is executed, the --train argument should be used to automatically download databases containing bugs and commits data.