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As someone working on a language myself, I found this to be very high-quality material! It aligns with a lot of my thinking, and it’s educational. A random pa

As someone working on a language myself, I found this to be very high-quality material! It aligns with a lot of my thinking, and it’s educational. A random part of interest: I followed the link about how linear types and exceptions don’t mix: https://borretti.me/article/linear-types-exceptions https://borretti.me/article/linear-types-exceptions In it, the author explains how linear types always need to be explicitly destroyed, and if you end up in a “catch” block, you can’t easily go back and destroy things that are now out of scope, which control flow got interrupted while doing things with. “Why not just destroy things when they go out of scope?” I thought. The author addresses this, saying that types that you have to “consume” “at most once” are called affine types, and the compiler can clean them up for you, and it solves the problem with exceptions. Rust has affine types, and you don’t have to explicitly “destruct” every string/object/resource using the appropriate destructor for that type, manually, as you do with linear types (of course, the compiler will make sure you do it, but you have to do it). So why does Austral use linear types, not affine types? The reasons given do not really resonate with me (but I’m not a systems programmer); it’s that the compiler would have to insert hidden function calls, and secondarily, for temporary/intermediate values, the order of invocation might not be obvious; plus, maybe the programmer not doing something with a value is a mistake. I’m really glad the reasons are written out, however. In other areas I feel very aligned with the author, such as on the value of required type annotations and local inference rather than global inference, and I’ve saved the link to refer back to the way the opinion is stated.

mamcx 3y ago
> So why does Austral use linear types, not affine types? Because linear types are simpler. The major reason here is that you don't need a "fancy" inference engine of lifetimes like the Rust borrow checker.
- Rusky 3y ago
  You don't need lifetimes or lifetime inference for affine types, either. Lifetimes/regions/borrowing are an orthogonal extension that you can add on top of either affine or linear types. (In fact Austral includes a region/borrowing system as well! It is a bit more explicit than Rust, along the lines of Rust's pre-NLL borrow checker, and with concrete binding forms instead of inference for regions, but this is also unrelated to the affine/linear distinction.) One reason for linear types over automatic scope-based destruction is that the final destruction can take arguments and produce results in a more streamlined way. This is nice for e.g. handling errors on file close.
  - treyd 3y ago
    One thing with explicit drops that Rust is having is that the thread can get SIGKILLed at any point without running destructors, which can complicate sync primitives and cause deadlocks in other threads if RAII is used for that. People do use it for that effectively but even if you have support for explicit drops it's really hard to ensure they actually run.
    - crabmusket 3y ago
      I can't quite parse your first line or two. Are you saying that explicit drops make SIGKILL a problem because the compiler can't automatically add in the right cleanups? Whereas if the compiler is in charge of adding all the drops, it can insert those into a signal handler?
      - Rusky 3y ago
        Rust certainly doesn't insert automatic cleanup in signal handlers. I don't think there's actually any meaningful difference between linear types and automatic drop here.
  - throwup238 3y ago
    > One reason for linear types over automatic scope-based destruction is that the final destruction can take arguments and produce results in a more streamlined way. This is nice for e.g. handling errors on file close. Couldn't the language allow something like Zig's `defer` op except tie that explicit destructor to the type?
    - _dain_ 3y ago
      Because it doesn't have to be something you'd ordinarily think of as a "destructor". e.g. you might have multiple possible functions that consume the value, because you're modelling a state machine with several outgoing edges from the type-state. You get to choose the one you call.
      - 3y ago
- wredue 3y ago
  I very much doubt that linear types are simpler in a lot of cases. Do they look simpler in cheesy anecdotes? Sure. But again, graphs and linked structures come in the to fray and it’s immediately noticeable that there’s be some problems here. Or maybe I am crazy in thinking that “being forced to update every single link just cause one node updated” is a problem. Even if this is only superficial, I foresee there being not insignificantly annoying issues in how one needs to manage graph and linked structures.
  - swsieber 3y ago
    My reading was that it is simpler to implement..
  - crabmusket 3y ago
    I think the point is they're simpler to specify and implement, and easier for the programmer to understand- not that they result in simpler code necessarily. From the language rationale: > Is it simple? Yes: the type system rules fit in a napkin. There’s no need to use an SMT solver, or to prove theorems about the code, or do symbolic execution and explore the state space of the program. The linearity checks are simple: we go over the code and count the number of times a variable appears, taking care to handle loops and if statements correctly. And also we ensure that linear values can’t be discarded silently. https://austral-lang.org/spec/spec.html#rationale-linear-types https://austral-lang.org/spec/spec.html#rationale-linear-typ...
deleted 3y ago
[deleted]
JonChesterfield 3y ago
Linear types are more powerful than affine in terms of implementing code that cannot go wrong as enforced by the type system. State machines reified in application code. Affine is fine if there's a catch all operation available for when the value drops out of scope which the compiler inserts. You can call deallocate or similar when an exception comes through the call stack. If the final operation is some function that returns something significant, takes extra arguments, interacts with the rest of the program in some sort of must-happen sense, then calling a destructor implicitly doesn't cover it. There's some interesting ideas around associating handlers with functions to deal with exceptions passing through but I think I've only seen that in one language. The simple/easy approach is to accept that exceptions and linear types are inconsistent.
- fdupress 3y ago
  Linear types and handlers are even more inconsistent, given the continuations could be run more than once if not careful.
  - alexisread 3y ago
    This is why, in Koka, there exists initially and finally blocks, to control resource cleanup https://koka-lang.github.io/koka/doc/book.html#sec-resource https://koka-lang.github.io/koka/doc/book.html#sec-resource I think linear types and exceptions can play well together if you use controlled effects like this.
- Rusky 3y ago
  One way you can think of the exception unwinding stuff is that each call provides not just one continuation (the usual return address) but two (also one for the cleanup), and that these are combined using the & connective of linear logic. This means both paths must use the same set of resources, and exactly one of them must be invoked. Interestingly, in linear logic this is equivalent (using De Morgan dualities) to a single continuation that expects a sum type: A^⊥ & B^⊥ = (A ⊕ B)^⊥.
  - JonChesterfield 3y ago
_dain_ 3y ago
>So why does Austral use linear types, not affine types? Affine types give a safety guarantee: you can't use it more than once. The bad thing (double free, use after free) does not happen. Linear types give that same safety guarantee, plus a liveness guarantee: you must use it, possibly in some nontrivial way. A function that takes an affine value as an argument is enforcing a contract about the past behaviour of the caller, leading up to the call: having the affine value is proof that certain other functions were called in the right way to produce it. But returning an affine value gives you weaker guarantees about future behaviour, because you can use it zero times. At most you know that it will get Dropped. But maybe you want to enforce more interesting things than the Drop trait can express. Returning a linear value lets you do this: maybe the linear Foo you return can only be disposed of in conjunction with a linear Bar, like fn consume(x: Foo, y: Bar) -> Baz And perhaps now Baz itself is linear, which has to be consumed in some other way ... at any rate, returning a linear value is proof that in the future, the program will advance through a particular state machine of function calls, where the states and transitions are defined by the available signatures. If Foo is linear but there's no simple function like fn drop(x: Foo) -> Unit then buckle in, the compiler says you're not getting off the ride until it's over.
- skybrian 3y ago
  It seems like a language could support both. That is, a type could either be automatically droppable or not.
  - dgreensp 3y ago
    Yes, this. The notable thing in Austral is not that linear types are used somewhere, it’s that it’s all linear, even when destruction is just deallocation and could easily be done by the compiler (even in the presence of exceptions).
    - _dain_ 3y ago
      You might want finer-grained control over when deallocation happens.
seanmcdirmid 3y ago
You can destroy them if you know they weren't destroyed in the try block. If they are destroyed in the the try block, then they would be in a dreaded "maybe destroyed" state. What you really want to do is somehow destroy resources in finally blocks. This is true if you are using linear types are not actually, and need to work with things that are explicitly destroyed.

mamcx 3y ago

> So why does Austral use linear types, not affine types? Because linear types are simpler. The major reason here is that you don't need a "fancy" inference engine of lifetimes like the Rust borrow checker.

Rusky 3y ago
You don't need lifetimes or lifetime inference for affine types, either. Lifetimes/regions/borrowing are an orthogonal extension that you can add on top of either affine or linear types. (In fact Austral includes a region/borrowing system as well! It is a bit more explicit than Rust, along the lines of Rust's pre-NLL borrow checker, and with concrete binding forms instead of inference for regions, but this is also unrelated to the affine/linear distinction.) One reason for linear types over automatic scope-based destruction is that the final destruction can take arguments and produce results in a more streamlined way. This is nice for e.g. handling errors on file close.
- treyd 3y ago
  One thing with explicit drops that Rust is having is that the thread can get SIGKILLed at any point without running destructors, which can complicate sync primitives and cause deadlocks in other threads if RAII is used for that. People do use it for that effectively but even if you have support for explicit drops it's really hard to ensure they actually run.
  - crabmusket 3y ago
    I can't quite parse your first line or two. Are you saying that explicit drops make SIGKILL a problem because the compiler can't automatically add in the right cleanups? Whereas if the compiler is in charge of adding all the drops, it can insert those into a signal handler?
    - Rusky 3y ago
      Rust certainly doesn't insert automatic cleanup in signal handlers. I don't think there's actually any meaningful difference between linear types and automatic drop here.
- throwup238 3y ago
  > One reason for linear types over automatic scope-based destruction is that the final destruction can take arguments and produce results in a more streamlined way. This is nice for e.g. handling errors on file close. Couldn't the language allow something like Zig's `defer` op except tie that explicit destructor to the type?
  - _dain_ 3y ago
    Because it doesn't have to be something you'd ordinarily think of as a "destructor". e.g. you might have multiple possible functions that consume the value, because you're modelling a state machine with several outgoing edges from the type-state. You get to choose the one you call.
    - 3y ago
wredue 3y ago
I very much doubt that linear types are simpler in a lot of cases. Do they look simpler in cheesy anecdotes? Sure. But again, graphs and linked structures come in the to fray and it’s immediately noticeable that there’s be some problems here. Or maybe I am crazy in thinking that “being forced to update every single link just cause one node updated” is a problem. Even if this is only superficial, I foresee there being not insignificantly annoying issues in how one needs to manage graph and linked structures.
- swsieber 3y ago
  My reading was that it is simpler to implement..
- crabmusket 3y ago
  I think the point is they're simpler to specify and implement, and easier for the programmer to understand- not that they result in simpler code necessarily. From the language rationale: > Is it simple? Yes: the type system rules fit in a napkin. There’s no need to use an SMT solver, or to prove theorems about the code, or do symbolic execution and explore the state space of the program. The linearity checks are simple: we go over the code and count the number of times a variable appears, taking care to handle loops and if statements correctly. And also we ensure that linear values can’t be discarded silently. https://austral-lang.org/spec/spec.html#rationale-linear-types https://austral-lang.org/spec/spec.html#rationale-linear-typ...

deleted 3y ago

[deleted]

JonChesterfield 3y ago

Linear types are more powerful than affine in terms of implementing code that cannot go wrong as enforced by the type system. State machines reified in application code. Affine is fine if there's a catch all operation available for when the value drops out of scope which the compiler inserts. You can call deallocate or similar when an exception comes through the call stack. If the final operation is some function that returns something significant, takes extra arguments, interacts with the rest of the program in some sort of must-happen sense, then calling a destructor implicitly doesn't cover it. There's some interesting ideas around associating handlers with functions to deal with exceptions passing through but I think I've only seen that in one language. The simple/easy approach is to accept that exceptions and linear types are inconsistent.

fdupress 3y ago
Linear types and handlers are even more inconsistent, given the continuations could be run more than once if not careful.
- alexisread 3y ago
  This is why, in Koka, there exists initially and finally blocks, to control resource cleanup https://koka-lang.github.io/koka/doc/book.html#sec-resource https://koka-lang.github.io/koka/doc/book.html#sec-resource I think linear types and exceptions can play well together if you use controlled effects like this.
Rusky 3y ago
One way you can think of the exception unwinding stuff is that each call provides not just one continuation (the usual return address) but two (also one for the cleanup), and that these are combined using the & connective of linear logic. This means both paths must use the same set of resources, and exactly one of them must be invoked. Interestingly, in linear logic this is equivalent (using De Morgan dualities) to a single continuation that expects a sum type: A^⊥ & B^⊥ = (A ⊕ B)^⊥.
- JonChesterfield 3y ago

_dain_ 3y ago

>So why does Austral use linear types, not affine types? Affine types give a safety guarantee: you can't use it more than once. The bad thing (double free, use after free) does not happen. Linear types give that same safety guarantee, plus a liveness guarantee: you must use it, possibly in some nontrivial way. A function that takes an affine value as an argument is enforcing a contract about the past behaviour of the caller, leading up to the call: having the affine value is proof that certain other functions were called in the right way to produce it. But returning an affine value gives you weaker guarantees about future behaviour, because you can use it zero times. At most you know that it will get Dropped. But maybe you want to enforce more interesting things than the Drop trait can express. Returning a linear value lets you do this: maybe the linear Foo you return can only be disposed of in conjunction with a linear Bar, like fn consume(x: Foo, y: Bar) -> Baz And perhaps now Baz itself is linear, which has to be consumed in some other way ... at any rate, returning a linear value is proof that in the future, the program will advance through a particular state machine of function calls, where the states and transitions are defined by the available signatures. If Foo is linear but there's no simple function like fn drop(x: Foo) -> Unit then buckle in, the compiler says you're not getting off the ride until it's over.

skybrian 3y ago
It seems like a language could support both. That is, a type could either be automatically droppable or not.
- dgreensp 3y ago
  Yes, this. The notable thing in Austral is not that linear types are used somewhere, it’s that it’s all linear, even when destruction is just deallocation and could easily be done by the compiler (even in the presence of exceptions).
  - _dain_ 3y ago
    You might want finer-grained control over when deallocation happens.

seanmcdirmid 3y ago

You can destroy them if you know they weren't destroyed in the try block. If they are destroyed in the the try block, then they would be in a dreaded "maybe destroyed" state. What you really want to do is somehow destroy resources in finally blocks. This is true if you are using linear types are not actually, and need to work with things that are explicitly destroyed.