Mayil-AI / bugbug-21dec23

Mozilla Public License 2.0
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bugbug

Task Status codecov

Bugbug aims at leveraging machine learning techniques to help with bug and quality management, and other software engineering tasks (such as test selection and defect prediction).

Chat with us in the bugbug Matrix room.

More information on the Mozilla Hacks blog:

Data generated by BugBug to train the models can be used independently from BugBug. See the docs for details.

Classifiers

Setup and Prerequisites

Install the Python dependencies:

pip3 install -r requirements.txt

You may also need pip install -r test-requirements.txt. Depending on the parts of bugbug you want to run, you might need to install dependencies from other requirement files (find them with find . -name "*requirements*").

Currently, Python 3.10+ is required. You can double check the version we use by looking at setup.py.

Also, libgit2 (needs v1.0.0, only in experimental on Debian), might be required (if you can't install it, skip this step).

sudo apt-get -t experimental install libgit2-dev

Auto-formatting

This project is using pre-commit. Please run pre-commit install to install the git pre-commit hooks on your clone.

Every time you will try to commit, pre-commit will run checks on your files to make sure they follow our style standards and they aren't affected by some simple issues. If the checks fail, pre-commit won't let you commit.

Usage

Training

Run the trainer.py script with the command python -m scripts.trainer (with --help to see the required and optional arguments of the command) to perform training (warning this takes 30min+).

Testing

To use a model to classify a given bug, you can run python -m scripts.bug_classifier MODEL_NAME --bug-id ID_OF_A_BUG_FROM_BUGZILLA. N.B.: If you run the classifier script without training a model first, it will automatically download an already trained model.

Example for the "defect" model

training To train the model for mode defect:

python3 -m scripts.trainer defect

testing To use the model to classify a given bug, you can run python -m scripts.bug_classifier defect --bug-id ID_OF_A_BUG_FROM_BUGZILLA.

Training on Taskcluster (Mozilla's CI platform)

You could run the model training task on the CI. To do this, simply include Train on Taskcluster: <model name> in the pull request description.

Example

To train the spambug model on Taskcluster, you need to add the following line in the pull request description, ideally at the bottom:

Train on Taskcluster: spambug

There are a few things to consider when training a model on Taskcluster:

Running the repository mining script

Note: This section is only necessary if you want to perform changes to the repository mining script. Otherwise, you can simply use the commits data we generate automatically.

  1. Clone https://hg.mozilla.org/mozilla-central/.
  2. Run ./mach vcs-setup in the directory where you have cloned mozilla-central.
  3. Enable the extensions mentioned in infra/hgrc. For example, if you are on Linux, you can add firefoxtree to the extensions section of the ~/.hgrc file as:
    firefoxtree = ~/.mozbuild/version-control-tools/hgext/firefoxtree
  4. Run the repository.py script, with the only argument being the path to the mozilla-central repository.

Note: If you run into problems, it's possible the version of Mercurial you are using is not supported. Check the Docker definition at infra/dockerfile.commit_retrieval to see what we are using in production.

Note: the script will take a long time to run (on my laptop more than 7 hours). If you want to test a simple change and you don't intend to actually mine the data, you can modify the repository.py script to limit the number of analyzed commits. Simply add limit=1024 to the call to the log command.

Structure of the project

Using bugbug for non-Mozilla projects

Bugbug is focussing on Mozilla use-cases for Firefox, Bugzilla and GitHub. However, we will be happy to accept pull requests adding support for other projects or bug trackers.