If you’re only going to learn one concurrency paradigm, it has to be message passing, because that’s the only one that works between machines.

The only reason why people don’t see the similarities when it comes to in-process concurrency is that the request-response paradigm muddies the waters. Anyway, that’s the world we live, so people have to work around the N+1 problem and similar, living in a mixed sync-async world of pain :)

It’ll take at least a decade to fix, if we ever do.

> because that’s the only one that works between machines

There is a non-negligible number of problems that don't need multiple machines and are much easier to deal with using other concurrency paradigms. When the language forces only one model onto the developer, things are actually more complex than they need to be.

Yeah, I agree, but Go is allowing traditional mutices that work the same way (except the rwlock discrepancy as pointed out by the paper). Channels aren’t forced, just encouraged. There are cases where locks are preferable.

My main criticism against the paper is that what tipped the scales for concurrency bugs is the “blocking category” which of course is going to be higher with message passing since it’s a blocking paradigm. Locks only block until unlocked, and isn’t used as a general purpose signaling mechanism.

The “non-blocking” bugs are over represented by locks, which are generally more serious (non-deterministic data races vs deterministic deadlocks).

That said, I have criticism against Go as well. The decision to not implement structured concurrency (fire-and-forget goroutines) makes these deadlocks largely go unnoticed. If goroutines had ownership or scope, runtime detection a la ‘-race’ would help detect a lot of these bugs.