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---
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layout: doc-page
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title: CanThrow capabilities
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---
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This page describes a new, experimental scheme for exception checking. The scheme is
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enabled by the language import
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```scala
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import language.experimental.saferExceptions
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```
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## Why Exceptions?
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Exceptions are an ideal mechanism for error handling in many situations. They serve the intended purpose of propagating error conditions with a minimum of boilerplate. They cause zero overhead for the "happy path", which means they are very efficient as long as errors arise infrequently. Exceptions are also debug friendly, since they produce stack traces that can be inspected at the handler site. So one never has to guess where an erroneous condition originated.
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## Why Not Exceptions?
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However, exceptions in Scala 2 and many other languages are not reflected in the type system. This means that an essential part of the contract of a function - i.e. what exceptions can it produce? - is not statically checked. Most people acknowledge that this is a problem, but that so far the alternative of checked exceptions was just too painful to be considered. A good example are Java checked exceptions, which do the right thing in principle, but are widely hated since they are so difficult to deal with. So far, none of the successor languages that are modeled after Java or build on the JVM have copied this feature.
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## The Problem With Java's Checked Exceptions
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The main problem with Java's checked exception model is its inflexibility, which is due to lack of polymorphism. Consider for instance the `map` function which is declared on `List[A]` like this:
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```scala
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def map[B](f: A => B): List[B]
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```
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In the Java model, function `f` is not allowed to throw a checked exception. So the following call would be invalid:
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```scala
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xs.map(x => if x < limit then f(x) else throw LimitExceeded())
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```
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The only way around this would be to wrap the checked exception `LimitExceeded` in an unchecked `RuntimeException` that is caught at the callsite and unwrapped again. Something like this:
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```scala
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try
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xs.map(x => if x < limit then f(x) else throw Wrapper(LimitExceeded()))
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catch case Wrapper(ex) => throw ex
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```
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Ugh! No wonder checked exceptions in Java are not very popular.
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## Monadic Effects And Their Downsides
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So the dilemma is that exceptions are easy to use only as long as we forgo static type checking. This has caused many people in the Scala community to abandon exceptions altogether and to use an error monad like `Either` instead. But that alternative is not without its downsides either. It makes code a lot more complicated and harder to refactor. It means one is quickly confronted with the problem how to work with several monads. In general, dealing with one monad in Scala is straightforward but dealing with several ones at the same time is much less pleasant since monads don't compose. A great number of techniques have been proposed, implemented, and vigorously promoted to deal with this, from monad transformers, to free monads, to tagless final. But none of these techniques is universally liked; each introduces a complicated DSL that's hard to understand for non-experts, introduces runtime overheads, and makes debugging difficult. In the end, many prefer to work with a single "super-monad" instead that has error propagation built in alongside other aspects. An example of this is ZIO. This one-size fits all approach can work very nicely, even though (or is it because?) it represents a rigid and all-encompassing framework.
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## From Effects To Capabilities
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Why does `map` work so poorly with Java's checked exception model? It's because
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`map`'s signature limits function arguments to not throw checked exceptions. We could try to come up with a more polymorphic formulation of `map`. For instance, it could look like this:
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```scala
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def map[B, E](f: A => B canThrow E): List[E] canThrow E
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```
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This assumes a type `A canThrow E` to indicate computations of type `A` that can throw an exception of type `E`. But in practice the overhead of the additional type parameters makes this approach unappealing as well. Note in particular that we'd have to parameterize _every method_ that takes a function argument that way, so the added overhead of declaring all these exception types looks just like a sort of ceremony we would like to avoid.
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But there is a way to avoid the ceremony. Instead of concentrating on possible _effects_ such as "this code might throw an exception", concentrate on _capabilities_ such as "this code needs the capability to throw an exception". From a standpoint of expressiveness it's the same; they are just different formulations for the same underlying semantics. But capabilities are expressed as parameters whereas traditionally effects are expressed as some operator on the result type. It turns out this makes a big difference!
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In the _effects as capabilities_ model, an effect is expressed as an (implicit) parameter of a certain type. For exceptions we would expect parameters of type
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`CanThrow[E]` where `E` stands for the exception that can be thrown. Here is the definition of `CanThrow`:
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```scala
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erased class CanThrow[-E <: Exception]
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```
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This shows another Scala feature (also still experimental): `erased` definitions. Roughly speaking, values of an `erased` class do not generate runtime code; they are erased before code generation. This means that all `CanThrow` capabilities are compile-time only artifacts; they do not have a runtime footprint.
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Now, if the compiler sees a `throw Exc()` construct where `Exc` is a checked exception it will check that there is a capability of type `CanThrow[Exc]` that can be summoned as a given. It's a compile-time error if that's not the case.
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How can the capability be produced? There are several possibilities:
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Most often, the capability is produced by having a using clause `(using CanThrow[Exc])` in some enclosing scope. This roughly corresponds to a `throws` clause
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in Java. The analogy is even stronger since alongside `CanThrow` there is also the following type alias defined in the `scala` package:
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```scala
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infix type canThrow[R, +E <: Exception] = CanThrow[E] ?=> R
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```
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That is, `R canThrow E` is a context function type that takes an implicit `CanThrow[E]` parameter and that returns a value of type `R`. Therefore, a method written like this:
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```scala
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def m(x: T)(using CanThrow[E]): U
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```
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can alternatively expressed like this:
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```scala
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def m(x: T): U canThrow E
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```
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_Aside_: If we rename `canThrow` to `throws` we would have a perfect analogy with Java but unfortunately `throws` is already taken in Scala 2.13.
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The `CanThrow`/`canThrow` combo essentially propagates the `CanThrow` requirement outwards. But where are these capabilities created in the first place? That's in the `try` expression. Given a `try` like this:
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```scala
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try
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body
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catch
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case ex1: Ex1 => handler1
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...
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case exN: ExN => handlerN
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```
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the compiler generates capabilities for `CanThrow[Ex1]`, ..., `CanThrow[ExN]` that are in scope as givens in `body`. It does this by augmenting the `try` roughly as follows:
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```scala
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try
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erased given CanThrow[Ex1] = ???
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...
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erased given CanThrow[ExN] = ???
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body
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catch ...
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```
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Note that the right-hand side of all givens is `???` (undefined). This is OK since
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these givens are erased; they will not be executed at runtime.
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## An Example
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That's it. Let's see it in action in an example. First, add an import
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```scala
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import language.experimental.saferExceptions
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```
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to enable exception checking. Now, define an exception `LimitExceeded` and
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a function `f` like this:
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```scala
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val limit = 10e9
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class LimitExceeded extends Exception
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def f(x: Double): Double =
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if x < limit then f(x) else throw LimitExceeded())
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```
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You'll get this error message:
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```
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9 | if x < limit then x * x else throw LimitExceeded()
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| ^^^^^^^^^^^^^^^^^^^^^
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|The capability to throw exception LimitExceeded is missing.
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|The capability can be provided by one of the following:
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| - A using clause `(using CanThrow[LimitExceeded])`
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| - A `canThrow` clause in a result type such as `X canThrow LimitExceeded`
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| - an enclosing `try` that catches LimitExceeded
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|
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|The following import might fix the problem:
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|
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| import unsafeExceptions.canThrowAny
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```
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As the error message implies, you have to declare that `f` needs the capability to throw a `LimitExceeded` exception. The most concise way to do so is to add a `canThrow` clause:
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```scala
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def f(x: Double): Double canThrow LimitExceeded =
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if x < limit then f(x) else throw LimitExceeded())
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```
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Now put a call to `f` in a `try` that catches `LimitExceeded`:
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```scala
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@main def test(xs: Double*) =
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try println(xs.map(f).sum)
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catch case ex: LimitExceeded => println("too large")
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```
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Run the program with some inputs:
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```
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> scala test 1 2 3
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14.0
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> scala test
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0.0
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> scala test 1 2 3 100000000000
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too large
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```
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Everything typechecks and works as expected. But wait - we have called `map` without any ceremony! How did that work? Here's how the compiler sees the `test` function:
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```scala
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@main def test(xs: Double*) =
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try
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erased given ctl: CanThrow[LimitExceeded] = ???
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println(xs.map(x => f(x)(using ctl)).sum)
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catch case ex: LimitExceeded => println("too large")
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```
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The `CanThrow[LimitExceeded]` capability is passed in a `using` clause to `f`, since `f` requires it. Then the resulting closure is passed to `map`. The signature of `map` does not have to account for effects. It takes a closure as always, but that
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closure may refer to capabilities in its free variables. This means that `map` is
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already effect polymorphic even though we did not change its signature at all.
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So the takeaway is that the effects as capabilities model naturally provides for effect polymorphism which is something that other approaches struggle with.
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## Gradual Typing Via Imports
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Another advantage is that the model allows a gradual migration from current unchecked exceptions to safer exceptions. Imagine for a moment that `experimental.saferExceptions` is turned on everywhere. There would be lots of code that breaks since functions have not yet been properly annotated with `canThrow`. But it's easy to create an escape hatch that lets us ignore the breakages for a while: simply use the import
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```scala
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import scala.unsafeExceptions.canThrowAny
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```
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This will provide the `CanThrow` capability for any exception, and thereby allow
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all throws, no matter what the current state of `canThrow` declarations is. Here's the
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definition of `canThrowAny`:
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```scala
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package scala
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object unsafeExceptions:
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given canThrowAny: CanThrow[Exception] = ???
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```
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Of course, defining a global capability like this amounts to cheating. But the cheating is useful for gradual typing. The import could be used to migrate existing code, or to
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enable more fluid explorations of code. At the end of these migrations or explorations the import should be removed.
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One quite surprising aspect is that we have achieved exception checking without any special additions to the type system. We just need regular givens and context functions. Any runtime overhead is eliminated using `erased`. Compare with Java, which has a set of elaborate rules specifically for exception checking.
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## Caveats
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The capability model allows to declare and check the thrown exceptions of first-order code. But as it stands it does not give us enough mechanism to enforce the _absence_ of
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capabilities for arguments to higher-order functions. Consider a variant `pureMap`
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of `map` that should enforce that its argument does not throw exceptions or have any other effects (maybe because wants to reorder computations transparently). Right now
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we cannot enforce that since the function argument to `pureMap` can capture arbitrary
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capabilities in its free variables without them showing up in its type. One possible way to
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address this would be to introduce a pure function type (maybe written `A -> B`). Pure functions are not allowed to close over capabilities. Then `pureMap` could be written
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like this:
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```
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def pureMap(f: A -> B): List[B]
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```
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Another area where the lack of higher-order purity enforcement shows up is when capabilities escape from bounded scopes. Consider the following function
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```scala
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def escaped(xs: Double*): () => Int
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try () => xs.map(f).sum
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catch case ex: LimitExceeded => -1
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```
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With the system presented here, this function typechecks, with expansion
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```scala
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def escaped(xs: Double*): () => Int
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try
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given ctl: CanThrow[LimitExceeded] = ???
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() => xs.map(f(using ctl)).sum
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catch case ex: LimitExceeded => -1
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```
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But if you try to call `escaped` like this
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```scala
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val g = escaped(1, 2, 100000000)
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g()
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```
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the result will be a `LimitExceeded` exception thrown at the second line where `g` is called. What's missing is that `try` should enforce that the capabilities it generates
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do not escape as free variables in the result of its body.
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We are working on a new class of type systems that allow to track the free variables of values. Once that research matures, it will hopefully be possible to augment the language so that we can enforce the missing properties (and it would have many other applications besides).
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But even without these additional mechanisms, exception checking is already useful as it is. It allows to express and check the exceptions that can thrown from a function and to catch the large majority of errors that would otherwise arise. Existing unsafe exception code can be easily retrofitted. So it gives a clear path forward to improve code that uses exceptions.

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