oss_fan

This is an interactive visualization of Claude Code signed commits from its release in 2025 until last week.

We can see the diffusion curves at the city and country level - the data is based on activity of 2 million developers located to the city level from their profile information.

This paper shows that experienced coders are getting more out of AI than early career devs, even though the latter use it more.

Food for thought for the software career ladder

Open source software ecosystems consist of thousands of interdependent libraries, which users can combine to great effect. Recent work has pointed out two kinds of risks in these systems: that technical problems like bugs and vulnerabilities can spread through dependency links, and that relatively few developers are responsible for maintaining even the most widely used libraries. However, a more holistic diagnosis of systemic risk in software ecosystem should consider how these social and technical sources of risk interact and amplify one another. Motivated by the observation that the same individuals maintain several libraries within dependency networks, we present a methodological framework to measure risk in software ecosystems as a function of both dependencies and developers. In our models, a library’s chance of failure increases as its developers leave and as its upstream dependencies fail. We apply our method to data from the Rust ecosystem, highlighting several systemically important libraries that are overlooked when only considering technical dependencies. We compare potential interventions, seeking better ways to deploy limited developer resources with a view to improving overall ecosystem health and software supply chain resilience.

Data on how many devs are leaving Russia and where they are going.

Large dataset on all aspects of Rust

New paper trying to measure brain drain from Russia using GitHub data.