OS Distribution vs OS Development Index

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Releasing code on GitHub doesn't mean that the project will be properly maintained once company looses interest in it. Project survivability is better if in addition to "Open Source as a Distribution Model" the project also exhibits open governance and participation model, and helps people to socialize. In contrast, many companies who release code in open, are not interested to support external contributions and communicate with general public. Depending on such projects in a long term is risky.

The metric that shows the commitment of companies towards OS Distribution Model rather than open governance and development, could help not only with evaluation a solution as to be sustainable, but also with help with drafting more effective Open Source Policies in companies.

For researchers and initiatives, such as SustainOSS, it will also be beneficial to get deeper analysis into survivability and inclusiveness of projects with and without companies support. To draft the best practices is it necessary to know how many companies are committing only into their own repos, and how many of them collaborate with other companies and individual maintainers. This data then be used for further analysis if corporate sponsorships for the projects such as Django Foundation, PFS etc. provides more value than forking and maintaining own toolsets, and also can be used as an argument for business to support such foundations.

We are all interested in using maintained and secure solutions. It may happen that using open development models not only helps projects survive in a long term, but also provides secondary benefits, such as spreading good engineering practices, socializing and onboarding newcomers.

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Common issues with "Open Source as a Distribution" projects:

• Using proprietary dependencies to build and run the project (Use Postgres instead of MS SQL #2)

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Common issues with "Open Source as a Distribution" projects:

• Maintainers are unknown Google, Telegram.
• Contributions are not credited

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Common issues with "Open Source as a Distribution" projects:

• Communication occurs over private channels

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Common issues with "Open Source as a Distribution" projects:

• No code reviews
• PRs are not accepted

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Things above can probably be detected by algorithms. Exact probability can be calculated only by a Data Science person. )