This repository contains data and code (for visualization) used for paper publication
To run the jupyternotebook
navigate to the root directory:
[Step: 1]
-
create a .venv using following command
python3 -m venv venv -
Activate it (macOS/Linux)
source venv/bin/activate -
Deactivate it when done (at the end)
deactivate
We have abstracted the python code into .py files (present in src/ directory) to make jupyternotebook more presentatble (so you need to install dependencies separately) as well as one time in notebook as we defined the input file globally for all code imported in notebook.
[Step: 2]
- Install requirements
We used pipreqs to create requirements.txt file given this repository contains only the code
You can install requirements.txt using the below
pip install -r requirements.txt
[Step: 3]
- Jupyternotebook run cells in notebook/analysis.ipynb to get reproduciable tables that are used in the paper.
The Data collection method involved:
- https://github.com/SE-UP/joss-repo-miner (To collect repositories published on Journal for opensource software)
- https://github.com/SE-UP/auto-test-artifact (To collect artifacts related to use of pre-commit hooks and CI tools to run tests; this tool uses PyGitHub for collecting of artifacts using github API)
- https://github.com/SE-UP/testing_artifact_detector (To collect artifacts related to RQ1: test artifactrs and RQ2: test types artifacts; this tool uses clone based approach)