The seven programming ur-languages (2022) (madhadron.com)

(2022) and unfortunately advice to spend significant amounts of time in learning multiple languages is becoming rapidly redundant in the LLM age.

I might add another class of languages: those intended to express proofs, via the Curry-Howard correspondence. Lean is a primary example here. This could be considered a subclass of functional languages but it might be different enough to warrant a separate class. In particular, the purpose of these programs is to be checked; execution is only secondary.

there's a few more semantic families: verilog, petri nets and variants, Kahn process networks and dataflow machines, process calculi, reactive, term rewriting, constraint solvers/theorem provers (not the same with Prolog), probabilistic programming,

plus up and coming (actual production-ready) languages that don't fit perfectly in the 7 categories: unison, darklang, temporal dataflow, DBSP

It may feel like a little bit of cheating mentioning the above ones, as most are parallel to the regular von Neumann machine setup, but was meaning for a while to do an article with 'all ways we know how to compute (beyond von Neumann)'.

My favorite subject when studying CompSci (TU Delft) was called "Concepts of programming languages". We learned C, Scala (for functional) and Javascript (prototypes).

It made learning Elixir years later much easier.

We also had a course that basically summed up to programming agents to play Unreal Tournament in a language called GOAL which was based on Prolog.

For years I've wanted to use Prolog but could not figure out how. I ended up making a spellcheck to allow LLM's to iterate over and fix the dismal Papiamentu they generate.

This article is full of gross mistakes. For example it claims that Caml is "Cambridge ML" which is ridiculously false. Fact check every sentence. Really sad.

One correction I'd make to the article's taxonomy: Ruby is an object oriented language not an Algol. Its inspiration is Smalltalk, and much of the standard library naming comes from that route (eg collect rather than map).

Ruby is object oriented from the ground up. Everything (and I do mean everything) is an object, and method call is conceived as passing messages to objects.

While Ruby is most often compared to Python (an Algol), they come from very different evolutionary routes, and have converged towards the same point in the ecosystem. I think of Ruby as a cuddly Alpaca compared to Python's spitting camel.

I wrote something similar here: https://fmjlang.co.uk/blog/GroundBreakingLanguages.html

We agree on Algol, Lisp, Forth, APL, and Prolog. For ground-breaking functional language, I have SASL (St Andrews Static Language), which (just) predates ML, and for object oriented language, I have Smalltalk (which predates Self).

I also include Fortran, COBOL, SNOBOL (string processing), and Prograph (visual dataflow), which were similarly ground-breaking in different ways.

Folks might find the following useful for studying PLs;

1) Advanced Programming Language Design by Raphael Finkel - A classic (late 90s) book comparing a whole smorgasbord of languages.

2) Design Concepts in Programming Languages by Franklyn Turbak et al. - A comprehensive (and big) book on PL design.

3) Concepts, Techniques and Models of Computer Programming by Peter Van Roy et al. - Shows how to organically add different programming paradigms to a simple core language.

Previous discussion: https://news.ycombinator.com/item?id=35813496

Lots of us are having fun identifying our choice for missing family :)

One I might suggest is scripting languages, defined loosely by programming tools which dispatch high-level commands to act on data pipelines: sed, AWK, the sh family, Perl, PowerShell, Python and R as honorary members. In practice I might say SQL belongs here instead of under Prolog, but in theory of course SQL is like Prolog. Bourne shell might be the best representative, even if it's not the oldest.

AWK et al share characteristics from ALGOL and APL, but I feel they are very much their own thing. PowerShell is quite unique among modern languages.

C++ has Algol roots, but I think the C++ template metaprogramming style is an ur-language of its own. You could draw some parallels with ML maybe, but they came at it from a different direction.

We got to build mini versions of the first 4 languages (imperative, lisp, ML, Smalltalk) in the PL course at tufts which is now published as a textbook [1]. There used to be a prolog part that sadly got cut.

[1]: https://www.cambridge.org/ir/universitypress/subjects/comput...

I’ve very slowly been trying to do the “99 problems” list in each of these languages groups. It’s been a fun experience seeing the differences. Though I think I would need a larger, less algorithmic, project to really see each group’s strengths. Especially for the OOP group.

One thing the article didn’t touch on was SmallTalk’s live visual environment. It’s not a normal source code / text language.

    ~

I always enjoy these summaries. I took my bachelor of computer science in the early 1990s. It covered a language in most of these categories.

We didn't learn APL (Who is teaching the use of those custom keyboards to 100s of young students for one semester?)

The processing power of systems at the time made it clear which language classes were practically useful and usable for the time and which were not.

Prolog ran like a dog for even simple sets of logic.

We had the best internet access and pretty powerful desktop systems for the time.

I'm still curious why we didn't learn smalltalk. Could have been the difficulty of submitting and marking a system in a particular state rather than a file of code :)

    Smalltalk VM 

    Smalltalk image file 

    sources file (plain-text original source code file) 

    changes file (plain-text change log, initially empty)

Isn‘t FORTRAN also a ur-language? It was invented in 1957.

Plankalkül

Most old-timers here are familiar with a Prolog-variant: make. Anyone who's struggled over a complex Makefile wishes they had a more sane declarative language!

[dead]

I would add another to the list, which is languages where every expression yields zero or more values, particularly `jq`. there are some antecedents in Icon and xquery, but these generally require explicitly opting into either production or consumption of value streams, where jq does this stream processing automatically from the ground up. (icon requires use of a suspend and needs an every clause to walk the generated values, xquery requires explicit 'for' statements over streams as many builtin operators fail on value streams)

in jq, the comma separates expressions, which independently yield values. a span of such expressions is called a 'filter', since they are always run by passing values from the prior filter into them (with the initial values sourcing from json objects on stdin, or an implicit null if you pass -n to the program).

    $ jq -nc ' def x: "a", "b", "c" ; def y: 1, 2, 3 ; x, y '
    "a"
    "b"
    "c"
    1
    2
    3

    $ jq -c '. + 10, . + 20' <<< '1 2 3'
    11
    21
    12
    22
    13
    23

brackets collect values yielded inside of them.

    $ jq -nc ' def x: "a", "b", "c" ; def y: 1, 2, 3 ; [x,y] '
    ["a","b","c",1,2,3]

if you have a complex object that includes multiple expressions yielding multiple values, construction will permute over them.

    $ jq -nc ' def x: "a", "b", "c" ; def y: 1, 2, 3 ; {"foo": x, "bar": y} '
    {"foo":"a","bar":1}
    {"foo":"a","bar":2}
    {"foo":"a","bar":3}
    {"foo":"b","bar":1}
    {"foo":"b","bar":2}
    {"foo":"b","bar":3}
    {"foo":"c","bar":1}
    {"foo":"c","bar":2}
    {"foo":"c","bar":3}

the pipe operator `|` runs the next filter with each value yielded by the prior, that value represented by the current value operator `.`.

    $ jq -nc ' 1,2,3 | 10 + . '
    11
    12
    13
    $ jq -nc ' 1,2,3 | (10 + .) * . '
    11
    24
    39

binding variables in the language is similarly done for each value their source yields

    $ jq -nc ' (1,2,3) as $A | $A + $A '
    2
    4
    6

functions in the language are neat because you can choose to accept arguments as either early bound values, or as thunks, with the former prefixed with a $.

for example, this runs `. + 100` parameters context, with `.` as the 10,20,30 passed to it:

    $ jq -nc ' def f($t): 1,2,3|$t ; 10,20,30|f(. + 100) '
    110
    110
    110
    120
    120
    120
    130
    130
    130

where this runs `. + 100` in the context of its use inside the function, instead receiving 1,2,3:

    $ jq -nc ' def f(t): 1,2,3|t ; 10,20,30|f(. + 100) '
    101
    102
    103
    101
    102
    103
    101
    102
    103

so you could define map taking a current-value array and applying an expression to each entry like so:

    $ jq -nc ' def m(todo): [.[]|todo] ; [1,2,3]|m(. * 10) '
    [10,20,30]

it's a fun little language for some quick data munging, but the semantics themselves are a decent reason to learn it.