Separating data structure from implementation has benefits.

In languages with classic OOP classes and objects, it’s often necessary to write wrappers or adapters to allow new operations on existing objects. This adds overhead and require more code.

XMPP, Conversations is a Nice Android client.

The headline and/or article is confusing. It says “machine learning library for the Linux kernel” but goes on to say it’s going to do ML in userspace.

It sounds like it’s going to be a process that lives outside the kernel and tunes the kernel via some interface. In which case there would be no need for any ML-specific bit in the kernel. Rather a generic interface to collect stats, tune thing. Processes would use those however they want, using ML or astrology or classic algorithms for their internal logic.

Write tests.