Johnni Winther
ac20881b23
This adds support for record types in the exhaustiveness algorithm.
The original algorithm was based on that record pattern would
match fields on all types, but that is no longer the case. Instead
record patterns only match corresponding to their own type. For this
reason the testing code is updated to create record spaces in relation
to a type. For instance, when the test create a record space {x: B}, it
is know create in relation to a type, say (x: A, y: A), and the create
space will therefore have (x: *, y: *) structure where the y: component
is implicitly Top, similar to how object patterns are used.
Unlike the Dart record types used for type checking and inference, the
record types used for exhaustiveness do not take the field types into
account for its subtype relation. This is avoid conclusions like
(int i, Object o) and (Object o, int i) having no values in common because
their corresponding types (int, Object) and (Object, int) are not subtypes
of each other. Instead, the subtype relation for record types used for
exhaustiveness only use the structure of the record to determine whether
two types are related.
Note though, that fields of a record type still know the type of the field.
This is used when expanded a record type into a space; the field spaces
will be derived from the field types in this case.
Change-Id: I84735d827494bcf384fd5f419d71933830ff5d15
Reviewed-on: https://dart-review.googlesource.com/c/sdk/+/283182
Reviewed-by: Paul Berry <paulberry@google.com>
Commit-Queue: Johnni Winther <johnniwinther@google.com>
Dart Kernel
Dart Kernel is a small high-level language derived from Dart. It is designed for use as an intermediate format for whole-program analysis and transformations, and to be consumed by codegen and execution backends.
The kernel language has an in-memory representation in Dart and can be serialized as binary or text.
Both the kernel language and its implementations are unstable and are under development.
This package contains the Dart part of the implementation and contains:
- A transformable IR for the kernel language
- Serialization of kernel code
Note: The APIs in this package are in an early state; developers should be careful about depending on this package. In particular, there is no semver contract for release versions of this package. Please depend directly on individual versions.
See ast.dart for the in-memory IR, or binary.md for a description of the binary format. For now, the textual format is very ad-hoc and cannot be parsed back in.