How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions

Reproduction Package for the Paper "How do Machine Learning Projects use Continuous Integration Practices? An Empirical Study on GitHub Actions"

This reproduction package contains the necessary materials to replicate the findings presented in the paper published at the Mining Software Repositories (MSR) conference in 2024.

Folder Structure:
- datasets: Contains all datasets used in the analysis of the Research Questions (RQs) of the paper.

- plots: Contains plots generated to present the results of the investigated RQs of the study.

- r-script: Contains all R scripts used in the analysis of the RQs, as well as scripts used to compute metrics such as build duration, time to fix broken builds, and test coverage.

- RQ3-neovis-network-graph: Contains a README.txt file providing instructions to create the network graph used to present the results of RQ3 using the neovisjs library.

Please refer to the specific folders for detailed information on how to reproduce the analysis and results presented in the paper.

Furthermore, the code we used to retrieve data for the studied projects is available in the following GitHub repository: https://github.com/joaohelis/ml-ci-project-miner