Self and Self: Whys and Wherefores

To get a feeling for the Self language and what was (is) possible, you should (if you can, of course) take the time to watch the video: ▶ this video It contains a few gems, and is really worthwhile watching. (Disclaimer, I think Dave Ungar has done tremendous things for PLDI; interested people should definitely check out his UC-Berkeley PhD thesis of 1986, easily one of the best I have ever seen...)

David Unger gave a great talk recently on this: ▶ this video (recorded at Stanford, but it's a reprise of his acceptance speech on receiving the Dahl-Nygaard award from memory) He has a role-call at the end of what the people involved in the self project went on to do afterwards, and it's staggering: some of the engineers of the original Google architecture, what became Hotspot as you say, Lars Bak (of Chrome V8) as someone else has pointed out... just an amazing list.

What was really interesting about Self was its optimizability - they were able to implement a Smalltalk on Self that was much faster than the contemporary Smalltalk systems. The impression I got from poking around at Self was that there was a class/inheritance system informally approximated in the prototypical relations of the objects and traits, but that doesn't mean you can't formally define one. For anyone curious, I recommend this talk [0] by David Ungar, one of Self's creators, that explains the history, philosophy, successes, and failures of the Self project. It's a shame more didn't get done with it (though V8, arguably the most important language runtime, is very similar). Someone has even been making a Zig version of Self recently [1]. [0] ▶ this video [1] link

[0] is Self and Self: Whys and Wherefores < ▶ this video > > And at the time, we thought it was impossible to make this language run efficiently, because it did all these things that were more abstract than languages of the time ...

Self and Self: Whys and Wherefores (September 30, 2009) David Unger, from IBM Research, discusses how his experience in computer science has led him to the conclusion that even if your ideas succeed, the real legacy is the people. ▶ this video