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f99e0e4 May 31, 2018
@aidanhs @ordovicia @aturon @alexcameron89
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Summary

  • Use inference to determine the variance of input type parameters.
  • Make it an error to have unconstrained type/lifetime parameters.
  • Revamp the variance markers to make them more intuitive and less numerous. In fact, there are only two: PhantomData and PhantomFn.
  • Integrate the notion of PhantomData into other automated compiler analyses, notably OIBIT, that can otherwise be deceived into yielding incorrect results.

Motivation

Why variance is good

Today, all type parameters are invariant. This can be problematic around lifetimes. A particular common example of where problems arise is in the use of Option. Here is a simple example. Consider this program, which has a struct containing two references:

struct List<'l> {
    field1: &'l int,
    field2: &'l int,
}

fn foo(field1: &int, field2: &int) {
    let list = List { field1: field1, field2: field2 };
    ...
}

fn main() { }

Here the function foo takes two references with distinct lifetimes. The variable list winds up being instantiated with a lifetime that is the intersection of the two (presumably, the body of foo). This is good.

If we modify this program so that one of those references is optional, however, we will find that it gets a compilation error:

struct List<'l> {
    field1: &'l int,
    field2: Option<&'l int>,
}

fn foo(field1: &int, field2: Option<&int>) {
    let list = List { field1: field1, field2: field2 };
        // ERROR: Cannot infer an appropriate lifetime
    ...
}

fn main() { }

The reason for this is that because Option is invariant with respect to its argument type, it means that the lifetimes of field1 and field2 must match exactly. It is not good enough for them to have a common subset. This is not good.

What variance is

Variance is a general concept that comes up in all languages that combine subtyping and generic types. However, because in Rust all subtyping is related to the use of lifetimes parameters, Rust uses variance in a very particular way. Basically, variance is a determination of when it is ok for lifetimes to be approximated (either made bigger or smaller, depending on context).

Let me give a few examples to try and clarify how variance works. Consider this simple struct Context:

struct Context<'data> {
    data: &'data u32,
    ...
}

Here the Context struct has one lifetime parameter, data, that represents the lifetime of some data that it references. Now let's imagine that the lifetime of the data is some lifetime we call 'x. If we have a context cx of type Context<'x>, it is ok to (for example) pass cx as an argment where a value of type Context<'y> is required, so long as 'x : 'y ("'x outlives 'y"). That is, it is ok to approximate 'x as a shorter lifetime like 'y. This makes sense because by changing 'x to 'y, we're just pretending the data has a shorter lifetime than it actually has, which can't do any harm. Here is an example:

fn approx_context<'long,'short>(t: &Context<'long>, data: &'short Data)
    where 'long : 'short
{
    // here we approximate 'long as 'short, but that's perfectly safe.
    let u: &Context<'short> = t;
    do_something(u, data)
}

fn do_something<'x>(t: &Context<'x>, data: &'x Data) {
   ...
}

This case has been traditionally called "contravariant" by Rust, though some argue (somewhat persuasively) that "covariant" is the better terminology. In any case, this RFC generally abandons the "variance" terminology in publicly exposed APIs and bits of the language, making this a moot point (in this RFC, however, I will stick to calling lifetimes which may be made smaller "contravariant", since that is what we have used in the past).

Next let's consider a struct with interior mutability:

struct Table<'arg> {
    cell: Cell<&'arg Foo>
}

In the case of Table, it is not safe for the compiler to approximate the lifetime 'arg at all. This is because 'arg appears in a mutable location (the interior of a Cell). Let me show you what could happen if we did allow 'arg to be approximated:

fn innocent<'long>(t: &Table<'long>) {
    {
        let foo: Foo = ..;
        evil(t, &foo);
    }
    t.cell.get() // reads `foo`, which has been destroyed
}

fn evil<'long,'short>(t: &Table<'long>, s: &'short Foo)
    where 'long : 'short
{
    // The following assignment is not legal, but it would be legal
    let u: &Table<'short> = t;
    u.cell.set(s);
}

Here the function evil() changes contents of t.cell to point at data with a shorter lifetime than t originally had. This is bad because the caller still has the old type (Table<'long>) and doesn't know that data with a shorter lifetime has been inserted. (This is traditionally called "invariant".)

Finally, there can be cases where it is ok to make a lifetime longer, but not shorter. This comes up (for example) in a type like fn(&'a u8), which may be safely treated as a fn(&'static u8).

Why variance should be inferred

Actually, lifetime parameters already have a notion of variance, and this variance is fully inferred. In fact, the proper variance for type parameters is also being inferred, we're just largely ignoring it. (It's not completely ignored; it informs the variance of lifetimes.)

The main reason we chose inference over declarations is that variance is rather tricky business. Most of the time, it's annoying to have to think about it, since it's a purely mechanical thing. The main reason that it pops up from time to time in Rust today (specifically, in examples like the one above) is because we ignore the results of inference and just make everything invariant.

But in fact there is another reason to prefer inference. When manually specifying variance, it is easy to get those manual specifications wrong. There is one example later on where the author did this, but using the mechanisms described in this RFC to guide the inference actually led to the correct solution.

The corner case: unused parameters and parameters that are only used unsafely

Unfortunately, variance inference only works if type parameters are actually used. Otherwise, there is no data to go on. You might think parameters would always be used, but this is not true. In particular, some types have "phantom" type or lifetime parameters that are not used in the body of the type. This generally occurs with unsafe code:

struct Items<'vec, T> { // unused lifetime parameter 'vec
    x: *mut T
}

struct AtomicPtr<T> { // unused type parameter T
    data: AtomicUint  // represents an atomically mutable *mut T, really
}

Since these parameters are unused, the inference can reasonably conclude that AtomicPtr<int> and AtomicPtr<uint> are interchangable: after all, there are no fields of type T, so what difference does it make what value it has? This is not good (and in fact we have behavior like this today for lifetimes, which is a common source of error).

To avoid this hazard, the RFC proposes to make it an error to have a type or lifetime parameter whose variance is not constrained. Almost always, the correct thing to do in such a case is to either remove the parameter in question or insert a marker type. Marker types basically inform the inference engine to pretend as if the type parameter were used in particular ways. They are discussed in the next section.

Revamping the marker types

The UnsafeCell type

As today, the UnsafeCell<T> type is well-known to rustc and is always considered invariant with respect to its type parameter T.

Phantom data

This RFC proposes to replace the existing marker types (CovariantType, ContravariantLifetime, etc) with a single type, PhantomData:

// Represents data of type `T` that is logically present, although the
// type system cannot see it. This type is covariant with respect to `T`.
struct PhantomData<T>;

An instance of PhantomData is used to represent data that is logically present, although the type system cannot see it. PhantomData is covariant with respect to its type parameter T. Here are some examples of uses of PhantomData from the standard library:

struct AtomicPtr<T> {
    data: AtomicUint,

    // Act as if we could reach a `*mut T` for variance. This will
    // make `AtomicPtr` *invariant* with respect to `T` (because `T` appears
    // underneath the `mut` qualifier).
    marker: PhantomData<*mut T>,
}

pub struct Items<'a, T: 'a> {
    ptr: *const T,
    end: *const T,

    // Act as if we could reach a slice `[T]` with lifetime `'a`.
    // Induces covariance on `T` and suitable variance on `'a`
    // (covariance using the definition from rfcs#391).
    marker: marker::PhantomData<&'a [T]>,
}

Note that PhantomData can be used to induce covariance, invariance, or contravariance as desired:

PhantomData<T>         // covariance
PhantomData<*mut T>    // invariance, but see "unresolved question"
PhantomData<Cell<T>>   // invariance
PhantomData<fn(T)>     // contravariant

Even better, the user doesn't really have to understand the terms covariance, invariance, or contravariance, but simply to accurately model the kind of data that the type system should pretend is present.

Other uses for phantom data. It turns out that phantom data is an important concept for other compiler analyses. One example is the OIBIT analysis, which decides whether certain traits (like Send and Sync) are implemented by recursively examining the fields of structs and enums. OIBIT should treat phantom data the same as normal fields. Another example is the ongoing work for removing the #[unsafe_dtor] annotation, which also sometimes requires a recursive analysis of a similar nature.

Phantom functions

One limitation of the marker type PhantomData is that it cannot be used to constrain unused parameters appearing on traits. Consider the following example:

trait Dummy<T> { /* T is never used here! */ }

Normally, the variance of a trait type parameter would be determined based on where it appears in the trait's methods: but in this case there are no methods. Therefore, we introduce two special traits that can be used to induce variance. Similarly to PhantomData, these traits represent parts of the interface that are logically present, if not actually present:

// Act as if there were a method `fn foo(A) -> R`. Induces contravariance on A
// and covariance on R.
trait PhantomFn<A,R>;

These traits should appear in the supertrait list. For example, the Dummy trait might be modified as follows:

trait Dummy<T> : PhantomFn() -> T { }

As you can see, the () notation can be used with PhantomFn as well.

Designating marker traits

In addition to phantom fns, there is a convenient trait MarkerTrait that is intended for use as a supertrait for traits that designate sets of types. These traits often have no methods and thus no actual uses of Self. The builtin bounds are a good example:

trait Copy : MarkerTrait { }
trait Sized : MarkerTrait { }
unsafe trait Send : MarkerTrait { }
unsafe trait Sync : MarkerTrait { }

MarkerTrait is not builtin to the language or specially understood by the compiler, it simply encapsulates a common pattern. It is implemented as follows:

trait MarkerTrait for Sized? : PhantomFn(Self) -> bool { }
impl<Sized? T> MarkerTrait for T { }

Intuitively, MarkerTrait extends PhantomFn(Self) because it is "as if" the traits were defined like:

trait Copy {
    fn is_copyable(&self) -> bool { true }
}

Here, the type parameter Self appears in argument position, which is contravariant.

Why contravariance? To see why contravariance is correct, you have to consider what it means for Self to be contravariant for a marker trait. It means that if I have evidence that T : Copy, then I can use that as evidence to show that U : Copy if U <: T. More formally:

(T : Copy) <: (U : Copy)   // I can use `T:Copy` where `U:Copy` is expected...
U <: T                     // ...so long as `U <: T`

More intuitively, it means that if a type T implements the marker, than all of its subtypes must implement the marker.

Because subtyping is exclusively tied to lifetimes in Rust, and most marker traits are orthogonal to lifetimes, it actually rarely makes a difference what choice you make here. But imagine that we have a marker trait that requires 'static (such as Send today, though this may change). If we made marker traits covariant with respect to Self, then &'static Foo : Send could be used as evidence that &'x Foo : Send for any 'x, because &'static Foo <: &'x Foo:

(&'static Foo : Send) <: (&'x Foo : Send) // if things were covariant...
&'static Foo <: &'x Foo                   // ...we'd have the wrong relation here

Interesting side story: the author thought that covariance would be correct for some time. It was only when attempting to phrase the desired behavior as a fn that I realized I had it backward, and quickly found the counterexample I give above. This gives me confidence that expressing variance in terms of data and fns is more reliable than trying to divine the correct results directly.

Detailed design

Most of the detailed design has already been covered in the motivation section.

Summary of changes required

  • Use variance results to inform subtyping of nominal types (structs, enums).
  • Use variance for the output type parameters on traits.
  • Input type parameters of traits are considered invariant.
  • Variance has no effect on the type parameters on an impl or fn; rather those are freshly instantiated at each use.
  • Report an error if the inference does not find any use of a type or lifetime parameter and that parameter is not bound in an associated type binding in some where clause.

These changes have largely been implemented. You can view the results, and the impact on the standard library, in this branch on nikomatsakis's repository. Note though that as of the time of this writing, the code is slightly outdated with respect to this RFC in certain respects (which will clearly be rectified ASAP).

Variance inference algorithm

I won't dive too deeply into the inference algorithm that we are using here. It is based on Section 4 of the paper "Taming the Wildcards: Combining Definition- and Use-Site Variance" published in PLDI'11 and written by Altidor et al. There is a fairly detailed (and hopefully only slightly outdated) description in the code as well.

Bivariance yields an error

One big change from today is that if we compute a result of bivariance as the variance for any type or lifetime parameter, we will report a hard error. The error message explicitly suggests the use of a PhantomData or PhantomFn marker as appropriate:

type parameter `T` is never used; either remove it, or use a
marker such as `std::kinds::marker::PhantomData`"

The goal is to help users as concretely as possible. The documentation on the phantom markers should also be helpful in guiding users to make the right choice (the ability to easily attach documentation to the marker type was in fact the major factor that led us to adopt marker types in the first place).

Rules for associated types

The only exception is when this type parameter is in fact an output that is implied by where clauses declared on the type. As an example of why this distinction is important, consider the type Map declared here:

struct Map<A,B,I,F>
where I : Iterator<Item=A>, F : FnMut(A) -> B
{
    iter: I,
    fn: F,
}

Neither the type A nor B are reachable from the fields declared within Map, and hence the variance inference for them results in bivariance. However, they are nonetheless constrained. In the case of the parameter A, its value is determined by the type I, and B is determined by the type F (note that RFC 587 makes the return type of FnMut an associated type).

The analysis to decide when a type parameter is implied by other type parameters is the same as that specified in RFC 447.

Future possibilities

Make phantom data and fns more first-class. One thing I would consider in the future is to integrate phantom data and fns more deeply into the language to improve usability. The idea would be to add a phantom keyword and then permit the explicit declaration of phantom fields and fns in structs and traits respectively:

// Instead of
struct Foo<T> {
    pointer: *mut u8,
    _marker: PhantomData<T>
}
trait MarkerTrait : PhantomFn(Self) {
}

// you would write:
struct Foo<T> {
    pointer: *mut u8,
    phantom T
}
trait MarkerTrait {
    phantom fn(Self);
}

Phantom fields would not need to be specified when creating an instance of a type and (being anonymous) could never be named. They exist solely to aid the analysis. This would improve the usability of phantom markers greatly.

Alternatives

Default to a particular variance when a type or lifetime parameter is unused. A prior RFC advocated for this approach, mostly because markers were seen as annoying to use. However, after some discussion, it seems that it is more prudent to make a smaller change and retain explicit declarations. Some factors that influenced this decision:

  • The importance of phantom data for other analyses like OIBIT.
  • Many unused lifetime parameters (and some unused type parameters) are in fact completely unnecessary. Defaulting to a particular variance would not help in identifying these cases (though a better dead code lint might).
  • There is no default that is always correct but invariance, and invariance is typically too strong.
  • Phantom type parameters occur relatively rarely anyhow.

Remove variance inference and use fully explicit declarations. Variance inference is a rare case where we do non-local inference across type declarations. It might seem more consistent to use explicit declarations. However, variance declarations are notoriously hard for people to understand. We were unable to come up with a suitable set of keywords or other system that felt sufficiently lightweight. Moreover, explicit annotations are error-prone when compared to the phantom data and fn approach (see example in the section regarding marker traits).

Unresolved questions

There is one significant unresolved question: the correct way to handle a *mut pointer. It was revealed recently that while the current treatment of *mut T is correct, it frequently yields overly conservative inference results in practice. At present the inference treats *mut T as invariant with respect to T: this is correct and sound, because a *mut represents aliasable, mutable data, and indeed the subtyping relation for *mut T is that *mut T <: *mut U if T=U.

However, in practice, *mut pointers are often used to build safe abstractions, the APIs of which do not in fact permit aliased mutation. Examples are Vec, Rc, HashMap, and so forth. In all of these cases, the correct variance is covariant -- but because of the conservative treatment of *mut, all of these types are being inferred to an invariant result.

The complete solution to this seems to have two parts. First, for convenience and abstraction, we should not be building safe abstractions on raw *mut pointers anyway. We should have several convenient newtypes in the standard library, like ptr::Unique, that can be used, which would also help for handling OIBIT conditions and NonZero optimizations. In my branch I have used the existing (but unstable) type ptr::Unique for the primary role, which is kind of an "unsafe box". Unique should ensure that it is covariant with respect to its argument.

However, this raises the question of how to implement Unique under the hood, and what to do with *mut T in general. There are various options:

  1. Change *mut so that it behaves like *const. This unfortunately means that abstractions that introduce shared mutability have a responsibility for add phantom data to that affect, something like PhantomData<*const Cell<T>>. This seems non-obvious and unnatural.

  2. Rewrite safe abstractions to use *const (or even usize) instead of *mut, casting to *mut only they have a &mut self method. This is probably the most conservative option.

  3. Change variance to ignore *mut referents entirely. Add a lint to detect types with a *mut T type and require some sort of explicit marker that covers T. This is perhaps the most explicit option. Like option 1, it creates the odd scenario that the variance computation and subtyping relation diverge.

Currently I lean towards option 2.