Factor: An impressive stack-based language environment
junglecoder.com
junglecoder.com
It certainly seems like a neat language, but I could never find enough beginner material to make any headway (not sure if anything has changed in the past few years).
There is a Google tech talk where Slava talks about Factor @ Google.
It gives an overview of using some Factor libraries and features. Some have bitrot by now but many still work.
IIRC, named local variables have been available as a library feature for a long time now, so you don't have to write in a concatenative style when it's cumbersome to do so.
The iOS situation is difficult, because Apple does not allow runtime compiled/loaded code in general. LispWorks pre-compiles Lisp code and one creates an App with the help of Apple's Xcode. LispWorks has still an Interpreter at runtime. Generally it is a very complete implementation of Common Lisp (minus the runtime compilation), but without a Lisp-based GUI library. They also had to write a special Garbage Collector for the 64bit ARM iOS. Seems like it was not possible to have their usually more advanced GC, which for example is available with their 64bit ARM Linux port of LispWorks.
https://developer.apple.com/app-store/review/guidelines/ specifically 2.5.2
> On iOS, V8 cannot run because the operating system forbids just-in-time compilation; so instead of V8, we use our own port of the ChakraCore engine, on top of the integration with Node that Microsoft created in Node.js on ChakraCore. ChakraCore has a well-optimized, pure interpreter mode which complies with iOS’ restrictions.
http://www.janeasystems.com/blog/node-js-meets-ios/
> Apple does not allow Just-In-Time compilation on iOS (except for its own JavaScriptCore engine).
So the claim is that Apple will not allow a third-party Javascript engine which provides a JIT - even though interpreted code engines are allowed and this is what their node.js version did.
My impression is also that this is a technical restriction.
Has that changed?
> ChakraCore has a well-optimized, pure interpreter mode which complies with iOS’ restrictions.
(Which does not include runtime-compilation.)
The ARM backend has bitrot now so no longer works.
There's a newer one called Kitten that is statically typed and uses term rewriting to allow for more normal syntax when you want. It's pretty cool. Too bad none of these languages will ever take off.
Reference counting is only used for heap allocated values and types that themselves reference values, like pairs and tables.
https://github.com/basic-gongfu/cixl/blob/master/src/cixl/bo...
The advantage of stack-based is that instructions need not tell where there arguments live, making them smaller (if you have 16 integer registers, for example, a simple “add register I to register j, store result in register k” instruction needs 12 bits to encode the values of i, j, and k. That’s quite a lot if your instructions are 16 bits)
The disadvantage is that you have to move data to where instructions expect to see it before you can do computations. That makes your code larger and slower.
Last I know needing more instructions to do the same is more of a problem than having smaller instructions solves (https://www.usenix.org/events/vee05/full_papers/p153-yunhe.p...), but that’s over 10 years old.
I'm sure they will at least inspire some good features in others.
Being stack-based doesn't help JVM efficiency. Modern JVM's take that bytecode and immediately translate it to some other non-stack-based form and then compile it. JVM bytecode is effectively a serialization format for syntax trees. (Stacks are a nice notation for serializing a tree.)
I suspect something like Julia's type system, with Bits types and Abstract types, would work perfectly here[0][1].
[0] https://docs.julialang.org/en/release-0.4/manual/types/#bits...
[1] https://docs.julialang.org/en/release-0.4/manual/types/#abst...
val (a,b): (Int, Int) = f(); g(b, a);
Now compare this to a concatenative program: f swap g
It's too easy to pass the two variables in incorrect order (forgetting to use swap, for example) when you are not forced to assign them local names.
People have investigated typing for stack-based languages before, [1] is a good overview. I've been implementing a dialect of Joy in Python and it turns out that it is pretty straight forward to implement type-inference and -checking.[2]
However, I recently realized that I was doing waaaay too much work. I reimplemented Joy in Prolog and got typing for free. Several pages of Python became two pages of Prolog and the interpreter is more powerful, I could go on. It's really weird being so excited on the one hand and so rueful on the other. This is so cool but I wasted so much time!
Anyhow, going by what you're saying the_grue about passing variables in the wrong order, I think you may have been going at it in the wrong way.
Using Joy and deriving new definitions with it I've only very occasionally had bugs related to "typos" in argument order of stack items. If you start with little pieces and build up stable conceptual interfaces as you go the process seems to flow and lead to correct code. It's like playing with Legos, or deriving a mathematical theorem.
[1] http://prl.ccs.neu.edu/blog/2017/03/10/type-inference-in-sta...
> It's really weird being so excited on the one hand and so rueful on the other. This is so cool but I wasted so much time!
I wouldn't be surprised if the whole struggle to create a Python implementation was necessary to get a clear enough picture of how it all comes together, which is why it then was so easy to re-implement it in a much fewer lines of code. That is how learning how to program works in my experience, at least. So don't be too hard on yourself there.
There was definitely some of that, but much less than you might think. The timeframe I'm talking about is a bit longer: a friend of mine tried to interest me in Prolog twenty years ago and the "penny has dropped" only now. Better late than never. But I estimate I may have wasted, outright wasted, three to five man-years of work. (I spend a lot of waking hour on programming, a lot.)
The impact of the realization is so severe that I've coined a new personal rule (the first in over a decade) to wit: Always use the highest-level language/system and only "drop-down" to a lesser paradigm if I absolutely have to (for efficiency or expressiveness.)
(The paradigm hierarchy being: Logical/Relational >= Functional >= Imperative)
I find myself pivoting from being an expert Python programmer to a tyro Prolog programmer. It's disorienting, exciting, it makes me giddy at moments. I'm already more productive, and it's easier to write bug-free code.
In the particular case of implementing Joy in Python and in Prolog, I had previously learned about Logic Programing and Unification by studying an implementation of miniKanren in Python[1], so I knew what I was doing when implementing the type inference. There even came a moment when I realized that I should reimplement in Kanren or Prolog if I wanted to do things like propagate constraints ("value types", etc...)
Then a link here on HN to "Logic Programming and Compiler Writing" by David H. D. Warren[2] finally pushed me to do it. I was in the middle of writing a compiler (to Python/Cython) for Joy and I realized that Warren's paper showed a better way.
Reimplementing Joy in Prolog was as simple as typing in descriptions of the basic relations, which are then already executable.
Something curious happened next. I went to reimplement the type inference code and when I had finished I realized that I had just reimplemented the interpreter. In other words, in Prolog, the interpreter and the type inferencer are the same thing.
(Also, ten pages of Python code became one page of Prolog.)