[marcosdumay]

You mean, Haskell developers ditch the functional idiom and use a more imperative one when they need it for performance? And yes, they do, and it works nicely. But it's not solving any problem with the functional paradigm.

Anyway, none of them is a problem with the semantics of FP. They are a problem of insufficient optimization. So they will probably get solved at some point.

[travisathougies]

ST is not 'imperative'. The monadic interface can look imperative sure, but then you can also use Applicative and friends and that's back to being functional. Of course, I prefer to think of what you call 'imperative' programming as function composition where >>= is the reverse of the 'normal' composition operator. Indeed, sequential imperative commands and function composition are isomorphic.

[marcosdumay]

Hum... You declare an state and go modifying it with an action after another. Looks quite imperative to me. The fact that it returns an interpreter instead of values is meaningless if it doesn't change the way you think about the program.

If you personally prefers to read it as the declaration of a program that given an state modifies it step by step, you can claim it's functional. But you are alone on that, the language even has specialized syntax to push people into reading the former, and anything minimally complex all but requires it.

[TuringTest]

travisathougies is not alone on that. Every one of us functional programmers worth their salt will consider a sequence of transformations from one state to the next as a functional program, as long as there are no side effects outside the current function that may transform state in ways that aren't declared in the types of the input and return values (which would break the referential transparency).

Functional Reactive programming (i.e. combining functions over streams of mutating objects) is essentially that, and it's a pure functional paradigm, quite popular in front-end web development (and I hear it's even creeping its way into the back-end).

[mrkeen]

The benefit is same-input -> same-output.

[marcosdumay]

Ok, let's get specific.

Here is an STM function: orElse :: STM a -> STM a -> STM a

It returns the first argument if there isn't any synchronicity problem, or the second if some other execution line conflicts with the first.

What exactly do you mean by "same input -> same output" and how exactly does a programmer thinks about that function on this way when composing it into an STM interpreter?

[travisathougies]

I think you should give the guy above the benefit of the doubt and restrict yourself to ST. IO and STM are different beasts, and still they're not imperative. The issue with IO and STM is global state. Mutation of global state can be done imperatively, as many imperative languages do. It can also be done functionally using monads to hide the affine types in a nice wrapper class in the absence of proper affine types or using proper affine type systems. Haskell choose the former. Other languages, like clean, choose the latter.

Same input -> same output is a nice property of referential integrity, which is a common thing we have in functional languages, but it is actually not due to the functional nature. Imperative languages can trivially be made to have this property by disallowing mutation of variables not in the immediate scope and restrict IO side effects (and maybe a few other straightforwards restrictions depending on the language in question).

With that out of the way. Same input -> same output holds for `orElse :: STM a -> STM a -> STM a`. However, you really have to expand out the types.

Here is the definition of STM (from https://hackage.haskell.org/package/base-4.15.0.0/docs/GHC-C...):

> newtype STM = STM (State# RealWorld -> (# State# RealWorld, a #))

So, `orElse` should behave the same as a function with this type:

> (State# RealWorld -> (# State# RealWorld, a #)) -> (State# RealWorld -> (# State# RealWorld, a #)) -> State# RealWorld -> (# State# RealWorld, a #)

Now, the definition of 'same input -> same output' is clear. Assuming the global state (State# RealWorld) is the same, then the output state will be the same. Actually, this is not a property of all languages, as most languages allow arbitrary side effects in any code. Haskell does not. This is the key property that makes STM easy in Haskell and difficult in other languages. Note that the 'State# RealWorld' is always handled linearly, so there is no possible way the same 'value' could be passed in twice. Again, hiding this behind a monad enforces that this value is handled linearly, since Haskell doesn't have linear types (or at least didn't when STM, ST, and IO were written).

[mrkeen]

I was referring to the ST monad which bts and travisathougies were talking about, not STM.

I mean that when you run ST code twice with the same input, you will get the same output. E.g., if I write (runST f) + (runST f), that's the same as 2 * (runST f), etc.

As for thinking, it means I don't use step-through debuggers ever, because I don't need the whole program to be in a certain state to watch what happens. I just grab the function, grab the input, and run it in isolation.

[marcosdumay]

Ouch, I read STM every time I looked at it.

None of what I said applies to ST.

[blablablerg]

Yep it it is called declarative.