The Ages of Programming Language Creators

Honestly, a naive compiler was trivial to write for a simple instruction set list. Making it performant and covering edge cases is another ball of wax. Doing it in hardware is even more fun

Everyone should try everything once. Especially in programming or mathematics, where stakes are very low.

I’ve never actually written a full compiler, although I’ve written several interpreters and DSLs (and even worked on a couple professionally). It’s on my list of things to do one day, but only for fun. I’ve been at this long enough to know I want know part of the 99% perspiration it takes to make a language popular and success- but I’m quite grateful to the people who do.

I've done it twice and didn't complete them both times. Does this count?

ROTFL, thank you for that laugh, this was spot on :)

Excellent point. I would add that in many other fields, large contributions can come from "prodigies", i.e. extremely young people who just happen to be geniuses on some topic. I am not sure we have seen any prodigies yet in the Programming Language space, but I would bet there will be one - the combination of highly intelligence, not being too stuck on a local maximum, and the lower barrier to entry since nearly all compilers became open source and most programming guides are free... all combine to make it a fertile ground for young people to experiment.

Scheme is a 49-year-old language, based on a 64-year-old language. What counts as an "old" language for you?

Emacs has emacs lisp?

Emacs in 1974 (when rms was around 21) used TECO, and it's only in the mid-1980s that GNU Emacs came about with Elisp. Other variants of Emacs used Lisp or (James Gosling's) Mocklisp.

jQuery's "selection lang" is just CSS. It's a pretty egregious inclusion. 

I understand why you included it, though. Great work.

Okay but all languages on the computer aren’t all programming languages. It’d be like having a list of fine dining places and putting McDonald’s on the list just because they serve food. The precision completely matters!

WTF

Tom indeed was a genius. A mad genius, but still, it counts. Not just anybody can come up with that stuff.

YAML literally is a superset of JSON - so you could just write the playbook in JSON...

Eurgh, that's so bad (from here)

[
  {
    "name": "My first play",
    "hosts": "myhosts",
    "tasks": [
      {
        "name": "Ping my hosts",
        "ansible.builtin.ping": null
      },
      {
        "name": "Print message",
        "ansible.builtin.debug": {
          "msg": "Hello world"
        }
      }
    ]
  }
]

You can make programming languages in JSON and in XML, but that doesn't make JSON and XML programming languages.

Python is written in ASCII (or whatever), but that doesn't make ASCII a programming language.

The 'info' is incredibly wrong.

This is my point. All you’re doing is nitpicking the naming. It is the least useful critique you could make of the data. If he had two entries, one for “eMacs lisp” and the other for “eMacs”, then I’d say something is wrong, but that’s not what it is. The meaning is clear and the critique does not change the implications of the analysis in any way. Y’all are bike shedding and it’s painful to watch

Thank you!

I was expecting, say, at 55% probability my "second system effected" conjecture to be confirmed. I decided to program the corresponding statistics because I thought they should be somewhat of interest regardless...

It undermines the point when you talk about outliers (Crockford, Aaron Swartz), but they don't even fit the common definition of a language inventor. If those contributions count, then why not other significant pieces of software, which might reveal more outliers?

I think there are some issues with the way you present the data: Your algorithm doesn’t say which “broad categories” relate to which variable; That initial 5x multiplier is a magic number with no explanation; last, though you present the data, there’s no description of your collection methods. That last one is especially important, since they are all based on estimates how are we supposed to assume that the underlying data is correct? Looking at the raw rankings, i think it does probably come out looking more or less like I would expect, but it would give more confidence to speak on the data collection methods somewhere