Metrics Automated Release System

CHAOSS metrics have been defined to provide an in-depth view into the various features of an open-source project. The metrics are also a key input to help organizations strategically invest their resources.

M.A.R.S. (Metrics Automated Release System) aim is to automate & improve the metric release process. Keeping in mind the ever evolving CHAOSS, the system is scalable and flexible enough for easy tweaking in the future.

The final outcome is generation of reports for the metrics and their translations counterparts respectively.

M.A.R.S. supports Linux (Debian based) and MacOS based systems only.

Currently, it can be used to generate the reports of English, Spanish and Chinese version of the metrics that exist in the working groups and translations repositories.

There are two ways to run M.A.R.S:

• Using Docker
• Using Python virtual environment

Refer to this README to know more details about its usage.

The following image gives a high level overview of the workflow of M.A.R.S.

A rough walkthrough of the automation process:

• Select language through user input
• Load the corresponding yml config file
• Load the corresponding cover page and side scripts
• Create and/or cleanup the test_env directory
• Clone the WG and/or translations repositories
• Generate relative paths to metric markdown files in various WGs
• Pull all the metrics in base folder
• Make a common images directory
• Decrease heading levels (only in metric markdowns) by prepending ##
• Convert metrics markdown to tex
• Generate focus areas tables in tex (2 level hierarchy)
• Generate WG markdowns tex files for headings (3 level hierarchy)
• Add front and end matter
• Call pandoc to generate the final PDF
• Move the final PDF to the output directory
• Display success message and paths to log file and release PDF

The M.A.R.S project welcomes all kinds of contributions and suggestions. See CONTRIBUTING.md for more information.

This project has been made under Google Summer of Code '21

• Georg Link
• Jaskirat Singh
• Kevin Lumbard
• Matt Germonprez

• Ritik Malik
• Yash Prakash

Licensed under MIT License