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_match.rs
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/// Note: most tests relevant to this file can be found (at the time of writing)
/// in src/tests/ui/pattern/usefulness.
///
/// This file includes the logic for exhaustiveness and usefulness checking for
/// pattern-matching. Specifically, given a list of patterns for a type, we can
/// tell whether:
/// (a) the patterns cover every possible constructor for the type [exhaustiveness]
/// (b) each pattern is necessary [usefulness]
///
/// The algorithm implemented here is a modified version of the one described in:
/// http://moscova.inria.fr/~maranget/papers/warn/index.html
/// However, to save future implementors from reading the original paper, we
/// summarise the algorithm here to hopefully save time and be a little clearer
/// (without being so rigorous).
///
/// The core of the algorithm revolves about a "usefulness" check. In particular, we
/// are trying to compute a predicate `U(P, p)` where `P` is a list of patterns (we refer to this as
/// a matrix). `U(P, p)` represents whether, given an existing list of patterns
/// `P_1 ..= P_m`, adding a new pattern `p` will be "useful" (that is, cover previously-
/// uncovered values of the type).
///
/// If we have this predicate, then we can easily compute both exhaustiveness of an
/// entire set of patterns and the individual usefulness of each one.
/// (a) the set of patterns is exhaustive iff `U(P, _)` is false (i.e., adding a wildcard
/// match doesn't increase the number of values we're matching)
/// (b) a pattern `P_i` is not useful if `U(P[0..=(i-1), P_i)` is false (i.e., adding a
/// pattern to those that have come before it doesn't increase the number of values
/// we're matching).
///
/// During the course of the algorithm, the rows of the matrix won't just be individual patterns,
/// but rather partially-deconstructed patterns in the form of a list of patterns. The paper
/// calls those pattern-vectors, and we will call them pattern-stacks. The same holds for the
/// new pattern `p`.
///
/// For example, say we have the following:
/// ```
/// // x: (Option<bool>, Result<()>)
/// match x {
/// (Some(true), _) => {}
/// (None, Err(())) => {}
/// (None, Err(_)) => {}
/// }
/// ```
/// Here, the matrix `P` starts as:
/// [
/// [(Some(true), _)],
/// [(None, Err(()))],
/// [(None, Err(_))],
/// ]
/// We can tell it's not exhaustive, because `U(P, _)` is true (we're not covering
/// `[(Some(false), _)]`, for instance). In addition, row 3 is not useful, because
/// all the values it covers are already covered by row 2.
///
/// A list of patterns can be thought of as a stack, because we are mainly interested in the top of
/// the stack at any given point, and we can pop or apply constructors to get new pattern-stacks.
/// To match the paper, the top of the stack is at the beginning / on the left.
///
/// There are two important operations on pattern-stacks necessary to understand the algorithm:
/// 1. We can pop a given constructor off the top of a stack. This operation is called
/// `specialize`, and is denoted `S(c, p)` where `c` is a constructor (like `Some` or
/// `None`) and `p` a pattern-stack.
/// If the pattern on top of the stack can cover `c`, this removes the constructor and
/// pushes its arguments onto the stack. It also expands OR-patterns into distinct patterns.
/// Otherwise the pattern-stack is discarded.
/// This essentially filters those pattern-stacks whose top covers the constructor `c` and
/// discards the others.
///
/// For example, the first pattern above initially gives a stack `[(Some(true), _)]`. If we
/// pop the tuple constructor, we are left with `[Some(true), _]`, and if we then pop the
/// `Some` constructor we get `[true, _]`. If we had popped `None` instead, we would get
/// nothing back.
///
/// This returns zero or more new pattern-stacks, as follows. We look at the pattern `p_1`
/// on top of the stack, and we have four cases:
/// 1.1. `p_1 = c(r_1, .., r_a)`, i.e. the top of the stack has constructor `c`. We
/// push onto the stack the arguments of this constructor, and return the result:
/// r_1, .., r_a, p_2, .., p_n
/// 1.2. `p_1 = c'(r_1, .., r_a')` where `c ≠ c'`. We discard the current stack and
/// return nothing.
/// 1.3. `p_1 = _`. We push onto the stack as many wildcards as the constructor `c` has
/// arguments (its arity), and return the resulting stack:
/// _, .., _, p_2, .., p_n
/// 1.4. `p_1 = r_1 | r_2`. We expand the OR-pattern and then recurse on each resulting
/// stack:
/// S(c, (r_1, p_2, .., p_n))
/// S(c, (r_2, p_2, .., p_n))
///
/// 2. We can pop a wildcard off the top of the stack. This is called `D(p)`, where `p` is
/// a pattern-stack.
/// This is used when we know there are missing constructor cases, but there might be
/// existing wildcard patterns, so to check the usefulness of the matrix, we have to check
/// all its *other* components.
///
/// It is computed as follows. We look at the pattern `p_1` on top of the stack,
/// and we have three cases:
/// 1.1. `p_1 = c(r_1, .., r_a)`. We discard the current stack and return nothing.
/// 1.2. `p_1 = _`. We return the rest of the stack:
/// p_2, .., p_n
/// 1.3. `p_1 = r_1 | r_2`. We expand the OR-pattern and then recurse on each resulting
/// stack.
/// D((r_1, p_2, .., p_n))
/// D((r_2, p_2, .., p_n))
///
/// Note that the OR-patterns are not always used directly in Rust, but are used to derive the
/// exhaustive integer matching rules, so they're written here for posterity.
///
/// Both those operations extend straightforwardly to a list or pattern-stacks, i.e. a matrix, by
/// working row-by-row. Popping a constructor ends up keeping only the matrix rows that start with
/// the given constructor, and popping a wildcard keeps those rows that start with a wildcard.
///
///
/// The algorithm for computing `U`
/// -------------------------------
/// The algorithm is inductive (on the number of columns: i.e., components of tuple patterns).
/// That means we're going to check the components from left-to-right, so the algorithm
/// operates principally on the first component of the matrix and new pattern-stack `p`.
/// This algorithm is realised in the `is_useful` function.
///
/// Base case. (`n = 0`, i.e., an empty tuple pattern)
/// - If `P` already contains an empty pattern (i.e., if the number of patterns `m > 0`),
/// then `U(P, p)` is false.
/// - Otherwise, `P` must be empty, so `U(P, p)` is true.
///
/// Inductive step. (`n > 0`, i.e., whether there's at least one column
/// [which may then be expanded into further columns later])
/// We're going to match on the top of the new pattern-stack, `p_1`.
/// - If `p_1 == c(r_1, .., r_a)`, i.e. we have a constructor pattern.
/// Then, the usefulness of `p_1` can be reduced to whether it is useful when
/// we ignore all the patterns in the first column of `P` that involve other constructors.
/// This is where `S(c, P)` comes in:
/// `U(P, p) := U(S(c, P), S(c, p))`
/// This special case is handled in `is_useful_specialized`.
///
/// For example, if `P` is:
/// [
/// [Some(true), _],
/// [None, 0],
/// ]
/// and `p` is [Some(false), 0], then we don't care about row 2 since we know `p` only
/// matches values that row 2 doesn't. For row 1 however, we need to dig into the
/// arguments of `Some` to know whether some new value is covered. So we compute
/// `U([[true, _]], [false, 0])`.
///
/// - If `p_1 == _`, then we look at the list of constructors that appear in the first
/// component of the rows of `P`:
/// + If there are some constructors that aren't present, then we might think that the
/// wildcard `_` is useful, since it covers those constructors that weren't covered
/// before.
/// That's almost correct, but only works if there were no wildcards in those first
/// components. So we need to check that `p` is useful with respect to the rows that
/// start with a wildcard, if there are any. This is where `D` comes in:
/// `U(P, p) := U(D(P), D(p))`
///
/// For example, if `P` is:
/// [
/// [_, true, _],
/// [None, false, 1],
/// ]
/// and `p` is [_, false, _], the `Some` constructor doesn't appear in `P`. So if we
/// only had row 2, we'd know that `p` is useful. However row 1 starts with a
/// wildcard, so we need to check whether `U([[true, _]], [false, 1])`.
///
/// + Otherwise, all possible constructors (for the relevant type) are present. In this
/// case we must check whether the wildcard pattern covers any unmatched value. For
/// that, we can think of the `_` pattern as a big OR-pattern that covers all
/// possible constructors. For `Option`, that would mean `_ = None | Some(_)` for
/// example. The wildcard pattern is useful in this case if it is useful when
/// specialized to one of the possible constructors. So we compute:
/// `U(P, p) := ∃(k ϵ constructors) U(S(k, P), S(k, p))`
///
/// For example, if `P` is:
/// [
/// [Some(true), _],
/// [None, false],
/// ]
/// and `p` is [_, false], both `None` and `Some` constructors appear in the first
/// components of `P`. We will therefore try popping both constructors in turn: we
/// compute U([[true, _]], [_, false]) for the `Some` constructor, and U([[false]],
/// [false]) for the `None` constructor. The first case returns true, so we know that
/// `p` is useful for `P`. Indeed, it matches `[Some(false), _]` that wasn't matched
/// before.
///
/// - If `p_1 == r_1 | r_2`, then the usefulness depends on each `r_i` separately:
/// `U(P, p) := U(P, (r_1, p_2, .., p_n))
/// || U(P, (r_2, p_2, .., p_n))`
///
/// Modifications to the algorithm
/// ------------------------------
/// The algorithm in the paper doesn't cover some of the special cases that arise in Rust, for
/// example uninhabited types and variable-length slice patterns. These are drawn attention to
/// throughout the code below. I'll make a quick note here about how exhaustive integer matching is
/// accounted for, though.
///
/// Exhaustive integer matching
/// ---------------------------
/// An integer type can be thought of as a (huge) sum type: 1 | 2 | 3 | ...
/// So to support exhaustive integer matching, we can make use of the logic in the paper for
/// OR-patterns. However, we obviously can't just treat ranges x..=y as individual sums, because
/// they are likely gigantic. So we instead treat ranges as constructors of the integers. This means
/// that we have a constructor *of* constructors (the integers themselves). We then need to work
/// through all the inductive step rules above, deriving how the ranges would be treated as
/// OR-patterns, and making sure that they're treated in the same way even when they're ranges.
/// There are really only four special cases here:
/// - When we match on a constructor that's actually a range, we have to treat it as if we would
/// an OR-pattern.
/// + It turns out that we can simply extend the case for single-value patterns in
/// `specialize` to either be *equal* to a value constructor, or *contained within* a range
/// constructor.
/// + When the pattern itself is a range, you just want to tell whether any of the values in
/// the pattern range coincide with values in the constructor range, which is precisely
/// intersection.
/// Since when encountering a range pattern for a value constructor, we also use inclusion, it
/// means that whenever the constructor is a value/range and the pattern is also a value/range,
/// we can simply use intersection to test usefulness.
/// - When we're testing for usefulness of a pattern and the pattern's first component is a
/// wildcard.
/// + If all the constructors appear in the matrix, we have a slight complication. By default,
/// the behaviour (i.e., a disjunction over specialised matrices for each constructor) is
/// invalid, because we want a disjunction over every *integer* in each range, not just a
/// disjunction over every range. This is a bit more tricky to deal with: essentially we need
/// to form equivalence classes of subranges of the constructor range for which the behaviour
/// of the matrix `P` and new pattern `p` are the same. This is described in more
/// detail in `split_grouped_constructors`.
/// + If some constructors are missing from the matrix, it turns out we don't need to do
/// anything special (because we know none of the integers are actually wildcards: i.e., we
/// can't span wildcards using ranges).
use self::Constructor::*;
use self::SliceKind::*;
use self::Usefulness::*;
use self::WitnessPreference::*;
use rustc_data_structures::captures::Captures;
use rustc_index::vec::Idx;
use super::{compare_const_vals, PatternFoldable, PatternFolder};
use super::{FieldPat, Pat, PatKind, PatRange};
use rustc_attr::{SignedInt, UnsignedInt};
use rustc_errors::ErrorReported;
use rustc_hir::def_id::DefId;
use rustc_hir::{HirId, RangeEnd};
use rustc_middle::mir::interpret::{truncate, AllocId, ConstValue, Pointer, Scalar};
use rustc_middle::mir::Field;
use rustc_middle::ty::layout::IntegerExt;
use rustc_middle::ty::{self, Const, Ty, TyCtxt, TypeFoldable, VariantDef};
use rustc_session::lint;
use rustc_span::{Span, DUMMY_SP};
use rustc_target::abi::{Integer, Size, VariantIdx};
use arena::TypedArena;
use smallvec::{smallvec, SmallVec};
use std::borrow::Cow;
use std::cmp::{self, max, min, Ordering};
use std::convert::TryInto;
use std::fmt;
use std::iter::{FromIterator, IntoIterator};
use std::ops::RangeInclusive;
crate fn expand_pattern<'a, 'tcx>(cx: &MatchCheckCtxt<'a, 'tcx>, pat: Pat<'tcx>) -> Pat<'tcx> {
LiteralExpander { tcx: cx.tcx, param_env: cx.param_env }.fold_pattern(&pat)
}
struct LiteralExpander<'tcx> {
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
}
impl<'tcx> LiteralExpander<'tcx> {
/// Derefs `val` and potentially unsizes the value if `crty` is an array and `rty` a slice.
///
/// `crty` and `rty` can differ because you can use array constants in the presence of slice
/// patterns. So the pattern may end up being a slice, but the constant is an array. We convert
/// the array to a slice in that case.
fn fold_const_value_deref(
&mut self,
val: ConstValue<'tcx>,
// the pattern's pointee type
rty: Ty<'tcx>,
// the constant's pointee type
crty: Ty<'tcx>,
) -> ConstValue<'tcx> {
debug!("fold_const_value_deref {:?} {:?} {:?}", val, rty, crty);
match (val, &crty.kind, &rty.kind) {
// the easy case, deref a reference
(ConstValue::Scalar(p), x, y) if x == y => {
match p {
Scalar::Ptr(p) => {
let alloc = self.tcx.alloc_map.lock().unwrap_memory(p.alloc_id);
ConstValue::ByRef { alloc, offset: p.offset }
}
Scalar::Raw { .. } => {
let layout = self.tcx.layout_of(self.param_env.and(rty)).unwrap();
if layout.is_zst() {
// Deref of a reference to a ZST is a nop.
ConstValue::Scalar(Scalar::zst())
} else {
// FIXME(oli-obk): this is reachable for `const FOO: &&&u32 = &&&42;`
bug!("cannot deref {:#?}, {} -> {}", val, crty, rty);
}
}
}
}
// unsize array to slice if pattern is array but match value or other patterns are slice
(ConstValue::Scalar(Scalar::Ptr(p)), ty::Array(t, n), ty::Slice(u)) => {
assert_eq!(t, u);
ConstValue::Slice {
data: self.tcx.alloc_map.lock().unwrap_memory(p.alloc_id),
start: p.offset.bytes().try_into().unwrap(),
end: n.eval_usize(self.tcx, ty::ParamEnv::empty()).try_into().unwrap(),
}
}
// fat pointers stay the same
(ConstValue::Slice { .. }, _, _)
| (_, ty::Slice(_), ty::Slice(_))
| (_, ty::Str, ty::Str) => val,
// FIXME(oli-obk): this is reachable for `const FOO: &&&u32 = &&&42;` being used
_ => bug!("cannot deref {:#?}, {} -> {}", val, crty, rty),
}
}
}
impl<'tcx> PatternFolder<'tcx> for LiteralExpander<'tcx> {
fn fold_pattern(&mut self, pat: &Pat<'tcx>) -> Pat<'tcx> {
debug!("fold_pattern {:?} {:?} {:?}", pat, pat.ty.kind, pat.kind);
match (&pat.ty.kind, &*pat.kind) {
(
&ty::Ref(_, rty, _),
&PatKind::Constant {
value:
Const {
val: ty::ConstKind::Value(val),
ty: ty::TyS { kind: ty::Ref(_, crty, _), .. },
},
},
) => Pat {
ty: pat.ty,
span: pat.span,
kind: box PatKind::Deref {
subpattern: Pat {
ty: rty,
span: pat.span,
kind: box PatKind::Constant {
value: Const::from_value(
self.tcx,
self.fold_const_value_deref(*val, rty, crty),
rty,
),
},
},
},
},
(
&ty::Ref(_, rty, _),
&PatKind::Constant {
value: Const { val, ty: ty::TyS { kind: ty::Ref(_, crty, _), .. } },
},
) => bug!("cannot deref {:#?}, {} -> {}", val, crty, rty),
(_, &PatKind::Binding { subpattern: Some(ref s), .. }) => s.fold_with(self),
(_, &PatKind::AscribeUserType { subpattern: ref s, .. }) => s.fold_with(self),
_ => pat.super_fold_with(self),
}
}
}
impl<'tcx> Pat<'tcx> {
pub(super) fn is_wildcard(&self) -> bool {
match *self.kind {
PatKind::Binding { subpattern: None, .. } | PatKind::Wild => true,
_ => false,
}
}
}
/// A row of a matrix. Rows of len 1 are very common, which is why `SmallVec[_; 2]`
/// works well.
#[derive(Debug, Clone)]
crate struct PatStack<'p, 'tcx>(SmallVec<[&'p Pat<'tcx>; 2]>);
impl<'p, 'tcx> PatStack<'p, 'tcx> {
crate fn from_pattern(pat: &'p Pat<'tcx>) -> Self {
PatStack(smallvec![pat])
}
fn from_vec(vec: SmallVec<[&'p Pat<'tcx>; 2]>) -> Self {
PatStack(vec)
}
fn from_slice(s: &[&'p Pat<'tcx>]) -> Self {
PatStack(SmallVec::from_slice(s))
}
fn is_empty(&self) -> bool {
self.0.is_empty()
}
fn len(&self) -> usize {
self.0.len()
}
fn head(&self) -> &'p Pat<'tcx> {
self.0[0]
}
fn to_tail(&self) -> Self {
PatStack::from_slice(&self.0[1..])
}
fn iter(&self) -> impl Iterator<Item = &Pat<'tcx>> {
self.0.iter().copied()
}
// If the first pattern is an or-pattern, expand this pattern. Otherwise, return `None`.
fn expand_or_pat(&self) -> Option<Vec<Self>> {
if self.is_empty() {
None
} else if let PatKind::Or { pats } = &*self.head().kind {
Some(
pats.iter()
.map(|pat| {
let mut new_patstack = PatStack::from_pattern(pat);
new_patstack.0.extend_from_slice(&self.0[1..]);
new_patstack
})
.collect(),
)
} else {
None
}
}
/// This computes `D(self)`. See top of the file for explanations.
fn specialize_wildcard(&self) -> Option<Self> {
if self.head().is_wildcard() { Some(self.to_tail()) } else { None }
}
/// This computes `S(constructor, self)`. See top of the file for explanations.
fn specialize_constructor(
&self,
cx: &mut MatchCheckCtxt<'p, 'tcx>,
constructor: &Constructor<'tcx>,
ctor_wild_subpatterns: &'p [Pat<'tcx>],
) -> Option<PatStack<'p, 'tcx>> {
let new_heads = specialize_one_pattern(cx, self.head(), constructor, ctor_wild_subpatterns);
new_heads.map(|mut new_head| {
new_head.0.extend_from_slice(&self.0[1..]);
new_head
})
}
}
impl<'p, 'tcx> Default for PatStack<'p, 'tcx> {
fn default() -> Self {
PatStack(smallvec![])
}
}
impl<'p, 'tcx> FromIterator<&'p Pat<'tcx>> for PatStack<'p, 'tcx> {
fn from_iter<T>(iter: T) -> Self
where
T: IntoIterator<Item = &'p Pat<'tcx>>,
{
PatStack(iter.into_iter().collect())
}
}
/// A 2D matrix.
#[derive(Clone)]
crate struct Matrix<'p, 'tcx>(Vec<PatStack<'p, 'tcx>>);
impl<'p, 'tcx> Matrix<'p, 'tcx> {
crate fn empty() -> Self {
Matrix(vec![])
}
/// Pushes a new row to the matrix. If the row starts with an or-pattern, this expands it.
crate fn push(&mut self, row: PatStack<'p, 'tcx>) {
if let Some(rows) = row.expand_or_pat() {
for row in rows {
// We recursively expand the or-patterns of the new rows.
// This is necessary as we might have `0 | (1 | 2)` or e.g., `x @ 0 | x @ (1 | 2)`.
self.push(row)
}
} else {
self.0.push(row);
}
}
/// Iterate over the first component of each row
fn heads<'a>(&'a self) -> impl Iterator<Item = &'a Pat<'tcx>> + Captures<'p> {
self.0.iter().map(|r| r.head())
}
/// This computes `D(self)`. See top of the file for explanations.
fn specialize_wildcard(&self) -> Self {
self.0.iter().filter_map(|r| r.specialize_wildcard()).collect()
}
/// This computes `S(constructor, self)`. See top of the file for explanations.
fn specialize_constructor(
&self,
cx: &mut MatchCheckCtxt<'p, 'tcx>,
constructor: &Constructor<'tcx>,
ctor_wild_subpatterns: &'p [Pat<'tcx>],
) -> Matrix<'p, 'tcx> {
self.0
.iter()
.filter_map(|r| r.specialize_constructor(cx, constructor, ctor_wild_subpatterns))
.collect()
}
}
/// Pretty-printer for matrices of patterns, example:
/// +++++++++++++++++++++++++++++
/// + _ + [] +
/// +++++++++++++++++++++++++++++
/// + true + [First] +
/// +++++++++++++++++++++++++++++
/// + true + [Second(true)] +
/// +++++++++++++++++++++++++++++
/// + false + [_] +
/// +++++++++++++++++++++++++++++
/// + _ + [_, _, tail @ ..] +
/// +++++++++++++++++++++++++++++
impl<'p, 'tcx> fmt::Debug for Matrix<'p, 'tcx> {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "\n")?;
let &Matrix(ref m) = self;
let pretty_printed_matrix: Vec<Vec<String>> =
m.iter().map(|row| row.iter().map(|pat| format!("{:?}", pat)).collect()).collect();
let column_count = m.iter().map(|row| row.len()).max().unwrap_or(0);
assert!(m.iter().all(|row| row.len() == column_count));
let column_widths: Vec<usize> = (0..column_count)
.map(|col| pretty_printed_matrix.iter().map(|row| row[col].len()).max().unwrap_or(0))
.collect();
let total_width = column_widths.iter().cloned().sum::<usize>() + column_count * 3 + 1;
let br = "+".repeat(total_width);
write!(f, "{}\n", br)?;
for row in pretty_printed_matrix {
write!(f, "+")?;
for (column, pat_str) in row.into_iter().enumerate() {
write!(f, " ")?;
write!(f, "{:1$}", pat_str, column_widths[column])?;
write!(f, " +")?;
}
write!(f, "\n")?;
write!(f, "{}\n", br)?;
}
Ok(())
}
}
impl<'p, 'tcx> FromIterator<PatStack<'p, 'tcx>> for Matrix<'p, 'tcx> {
fn from_iter<T>(iter: T) -> Self
where
T: IntoIterator<Item = PatStack<'p, 'tcx>>,
{
let mut matrix = Matrix::empty();
for x in iter {
// Using `push` ensures we correctly expand or-patterns.
matrix.push(x);
}
matrix
}
}
crate struct MatchCheckCtxt<'a, 'tcx> {
crate tcx: TyCtxt<'tcx>,
/// The module in which the match occurs. This is necessary for
/// checking inhabited-ness of types because whether a type is (visibly)
/// inhabited can depend on whether it was defined in the current module or
/// not. E.g., `struct Foo { _private: ! }` cannot be seen to be empty
/// outside it's module and should not be matchable with an empty match
/// statement.
crate module: DefId,
param_env: ty::ParamEnv<'tcx>,
crate pattern_arena: &'a TypedArena<Pat<'tcx>>,
}
impl<'a, 'tcx> MatchCheckCtxt<'a, 'tcx> {
crate fn create_and_enter<R>(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
module: DefId,
f: impl FnOnce(MatchCheckCtxt<'_, 'tcx>) -> R,
) -> R {
let pattern_arena = TypedArena::default();
f(MatchCheckCtxt { tcx, param_env, module, pattern_arena: &pattern_arena })
}
fn is_uninhabited(&self, ty: Ty<'tcx>) -> bool {
if self.tcx.features().exhaustive_patterns {
self.tcx.is_ty_uninhabited_from(self.module, ty, self.param_env)
} else {
false
}
}
// Returns whether the given type is an enum from another crate declared `#[non_exhaustive]`.
crate fn is_foreign_non_exhaustive_enum(&self, ty: Ty<'tcx>) -> bool {
match ty.kind {
ty::Adt(def, ..) => {
def.is_enum() && def.is_variant_list_non_exhaustive() && !def.did.is_local()
}
_ => false,
}
}
// Returns whether the given variant is from another crate and has its fields declared
// `#[non_exhaustive]`.
fn is_foreign_non_exhaustive_variant(&self, ty: Ty<'tcx>, variant: &VariantDef) -> bool {
match ty.kind {
ty::Adt(def, ..) => variant.is_field_list_non_exhaustive() && !def.did.is_local(),
_ => false,
}
}
}
#[derive(Copy, Clone, Debug, PartialEq, Eq)]
enum SliceKind {
/// Patterns of length `n` (`[x, y]`).
FixedLen(u64),
/// Patterns using the `..` notation (`[x, .., y]`).
/// Captures any array constructor of `length >= i + j`.
/// In the case where `array_len` is `Some(_)`,
/// this indicates that we only care about the first `i` and the last `j` values of the array,
/// and everything in between is a wildcard `_`.
VarLen(u64, u64),
}
impl SliceKind {
fn arity(self) -> u64 {
match self {
FixedLen(length) => length,
VarLen(prefix, suffix) => prefix + suffix,
}
}
/// Whether this pattern includes patterns of length `other_len`.
fn covers_length(self, other_len: u64) -> bool {
match self {
FixedLen(len) => len == other_len,
VarLen(prefix, suffix) => prefix + suffix <= other_len,
}
}
/// Returns a collection of slices that spans the values covered by `self`, subtracted by the
/// values covered by `other`: i.e., `self \ other` (in set notation).
fn subtract(self, other: Self) -> SmallVec<[Self; 1]> {
// Remember, `VarLen(i, j)` covers the union of `FixedLen` from `i + j` to infinity.
// Naming: we remove the "neg" constructors from the "pos" ones.
match self {
FixedLen(pos_len) => {
if other.covers_length(pos_len) {
smallvec![]
} else {
smallvec![self]
}
}
VarLen(pos_prefix, pos_suffix) => {
let pos_len = pos_prefix + pos_suffix;
match other {
FixedLen(neg_len) => {
if neg_len < pos_len {
smallvec![self]
} else {
(pos_len..neg_len)
.map(FixedLen)
// We know that `neg_len + 1 >= pos_len >= pos_suffix`.
.chain(Some(VarLen(neg_len + 1 - pos_suffix, pos_suffix)))
.collect()
}
}
VarLen(neg_prefix, neg_suffix) => {
let neg_len = neg_prefix + neg_suffix;
if neg_len <= pos_len {
smallvec![]
} else {
(pos_len..neg_len).map(FixedLen).collect()
}
}
}
}
}
}
}
/// A constructor for array and slice patterns.
#[derive(Copy, Clone, Debug, PartialEq, Eq)]
struct Slice {
/// `None` if the matched value is a slice, `Some(n)` if it is an array of size `n`.
array_len: Option<u64>,
/// The kind of pattern it is: fixed-length `[x, y]` or variable length `[x, .., y]`.
kind: SliceKind,
}
impl Slice {
/// Returns what patterns this constructor covers: either fixed-length patterns or
/// variable-length patterns.
fn pattern_kind(self) -> SliceKind {
match self {
Slice { array_len: Some(len), kind: VarLen(prefix, suffix) }
if prefix + suffix == len =>
{
FixedLen(len)
}
_ => self.kind,
}
}
/// Returns what values this constructor covers: either values of only one given length, or
/// values of length above a given length.
/// This is different from `pattern_kind()` because in some cases the pattern only takes into
/// account a subset of the entries of the array, but still only captures values of a given
/// length.
fn value_kind(self) -> SliceKind {
match self {
Slice { array_len: Some(len), kind: VarLen(_, _) } => FixedLen(len),
_ => self.kind,
}
}
fn arity(self) -> u64 {
self.pattern_kind().arity()
}
}
#[derive(Clone, Debug, PartialEq)]
enum Constructor<'tcx> {
/// The constructor of all patterns that don't vary by constructor,
/// e.g., struct patterns and fixed-length arrays.
Single,
/// Enum variants.
Variant(DefId),
/// Literal values.
ConstantValue(&'tcx ty::Const<'tcx>),
/// Ranges of integer literal values (`2`, `2..=5` or `2..5`).
IntRange(IntRange<'tcx>),
/// Ranges of floating-point literal values (`2.0..=5.2`).
FloatRange(&'tcx ty::Const<'tcx>, &'tcx ty::Const<'tcx>, RangeEnd),
/// Array and slice patterns.
Slice(Slice),
/// Fake extra constructor for enums that aren't allowed to be matched exhaustively.
NonExhaustive,
}
impl<'tcx> Constructor<'tcx> {
fn is_slice(&self) -> bool {
match self {
Slice(_) => true,
_ => false,
}
}
fn variant_index_for_adt<'a>(
&self,
cx: &MatchCheckCtxt<'a, 'tcx>,
adt: &'tcx ty::AdtDef,
) -> VariantIdx {
match *self {
Variant(id) => adt.variant_index_with_id(id),
Single => {
assert!(!adt.is_enum());
VariantIdx::new(0)
}
ConstantValue(c) => cx.tcx.destructure_const(cx.param_env.and(c)).variant,
_ => bug!("bad constructor {:?} for adt {:?}", self, adt),
}
}
// Returns the set of constructors covered by `self` but not by
// anything in `other_ctors`.
fn subtract_ctors(&self, other_ctors: &Vec<Constructor<'tcx>>) -> Vec<Constructor<'tcx>> {
if other_ctors.is_empty() {
return vec![self.clone()];
}
match self {
// Those constructors can only match themselves.
Single | Variant(_) | ConstantValue(..) | FloatRange(..) => {
if other_ctors.iter().any(|c| c == self) { vec![] } else { vec![self.clone()] }
}
&Slice(slice) => {
let mut other_slices = other_ctors
.iter()
.filter_map(|c: &Constructor<'_>| match c {
Slice(slice) => Some(*slice),
// FIXME(oli-obk): implement `deref` for `ConstValue`
ConstantValue(..) => None,
_ => bug!("bad slice pattern constructor {:?}", c),
})
.map(Slice::value_kind);
match slice.value_kind() {
FixedLen(self_len) => {
if other_slices.any(|other_slice| other_slice.covers_length(self_len)) {
vec![]
} else {
vec![Slice(slice)]
}
}
kind @ VarLen(..) => {
let mut remaining_slices = vec![kind];
// For each used slice, subtract from the current set of slices.
for other_slice in other_slices {
remaining_slices = remaining_slices
.into_iter()
.flat_map(|remaining_slice| remaining_slice.subtract(other_slice))
.collect();
// If the constructors that have been considered so far already cover
// the entire range of `self`, no need to look at more constructors.
if remaining_slices.is_empty() {
break;
}
}
remaining_slices
.into_iter()
.map(|kind| Slice { array_len: slice.array_len, kind })
.map(Slice)
.collect()
}
}
}
IntRange(self_range) => {
let mut remaining_ranges = vec![self_range.clone()];
for other_ctor in other_ctors {
if let IntRange(other_range) = other_ctor {
if other_range == self_range {
// If the `self` range appears directly in a `match` arm, we can
// eliminate it straight away.
remaining_ranges = vec![];
} else {
// Otherwise explicitly compute the remaining ranges.
remaining_ranges = other_range.subtract_from(remaining_ranges);
}
// If the ranges that have been considered so far already cover the entire
// range of values, we can return early.
if remaining_ranges.is_empty() {
break;
}
}
}
// Convert the ranges back into constructors.
remaining_ranges.into_iter().map(IntRange).collect()
}
// This constructor is never covered by anything else
NonExhaustive => vec![NonExhaustive],
}
}
/// This returns one wildcard pattern for each argument to this constructor.
///
/// This must be consistent with `apply`, `specialize_one_pattern`, and `arity`.
fn wildcard_subpatterns<'a>(
&self,
cx: &MatchCheckCtxt<'a, 'tcx>,
ty: Ty<'tcx>,
) -> Vec<Pat<'tcx>> {
debug!("wildcard_subpatterns({:#?}, {:?})", self, ty);
match self {
Single | Variant(_) => match ty.kind {
ty::Tuple(ref fs) => {
fs.into_iter().map(|t| t.expect_ty()).map(Pat::wildcard_from_ty).collect()
}
ty::Ref(_, rty, _) => vec![Pat::wildcard_from_ty(rty)],
ty::Adt(adt, substs) => {
if adt.is_box() {
// Use T as the sub pattern type of Box<T>.
vec![Pat::wildcard_from_ty(substs.type_at(0))]
} else {
let variant = &adt.variants[self.variant_index_for_adt(cx, adt)];
let is_non_exhaustive = cx.is_foreign_non_exhaustive_variant(ty, variant);
variant
.fields
.iter()
.map(|field| {
let is_visible = adt.is_enum()
|| field.vis.is_accessible_from(cx.module, cx.tcx);
let is_uninhabited = cx.is_uninhabited(field.ty(cx.tcx, substs));
match (is_visible, is_non_exhaustive, is_uninhabited) {
// Treat all uninhabited types in non-exhaustive variants as
// `TyErr`.
(_, true, true) => cx.tcx.types.err,
// Treat all non-visible fields as `TyErr`. They can't appear
// in any other pattern from this match (because they are
// private), so their type does not matter - but we don't want
// to know they are uninhabited.
(false, ..) => cx.tcx.types.err,
(true, ..) => {
let ty = field.ty(cx.tcx, substs);
match ty.kind {
// If the field type returned is an array of an unknown
// size return an TyErr.
ty::Array(_, len)
if len
.try_eval_usize(cx.tcx, cx.param_env)
.is_none() =>
{
cx.tcx.types.err
}
_ => ty,
}
}
}
})
.map(Pat::wildcard_from_ty)
.collect()
}
}
_ => vec![],
},
Slice(_) => match ty.kind {
ty::Slice(ty) | ty::Array(ty, _) => {
let arity = self.arity(cx, ty);
(0..arity).map(|_| Pat::wildcard_from_ty(ty)).collect()
}
_ => bug!("bad slice pattern {:?} {:?}", self, ty),
},
ConstantValue(..) | FloatRange(..) | IntRange(..) | NonExhaustive => vec![],
}
}
/// This computes the arity of a constructor. The arity of a constructor
/// is how many subpattern patterns of that constructor should be expanded to.
///
/// For instance, a tuple pattern `(_, 42, Some([]))` has the arity of 3.
/// A struct pattern's arity is the number of fields it contains, etc.
///
/// This must be consistent with `wildcard_subpatterns`, `specialize_one_pattern`, and `apply`.
fn arity<'a>(&self, cx: &MatchCheckCtxt<'a, 'tcx>, ty: Ty<'tcx>) -> u64 {
debug!("Constructor::arity({:#?}, {:?})", self, ty);
match self {
Single | Variant(_) => match ty.kind {
ty::Tuple(ref fs) => fs.len() as u64,
ty::Slice(..) | ty::Array(..) => bug!("bad slice pattern {:?} {:?}", self, ty),
ty::Ref(..) => 1,
ty::Adt(adt, _) => {
adt.variants[self.variant_index_for_adt(cx, adt)].fields.len() as u64
}
_ => 0,
},
Slice(slice) => slice.arity(),
ConstantValue(..) | FloatRange(..) | IntRange(..) | NonExhaustive => 0,
}
}
/// Apply a constructor to a list of patterns, yielding a new pattern. `pats`
/// must have as many elements as this constructor's arity.
///
/// This must be consistent with `wildcard_subpatterns`, `specialize_one_pattern`, and `arity`.
///
/// Examples:
/// `self`: `Constructor::Single`
/// `ty`: `(u32, u32, u32)`
/// `pats`: `[10, 20, _]`
/// returns `(10, 20, _)`
///
/// `self`: `Constructor::Variant(Option::Some)`
/// `ty`: `Option<bool>`
/// `pats`: `[false]`
/// returns `Some(false)`
fn apply<'a>(
&self,
cx: &MatchCheckCtxt<'a, 'tcx>,
ty: Ty<'tcx>,
pats: impl IntoIterator<Item = Pat<'tcx>>,
) -> Pat<'tcx> {
let mut subpatterns = pats.into_iter();
let pat = match self {
Single | Variant(_) => match ty.kind {
ty::Adt(..) | ty::Tuple(..) => {
let subpatterns = subpatterns
.enumerate()
.map(|(i, p)| FieldPat { field: Field::new(i), pattern: p })
.collect();
if let ty::Adt(adt, substs) = ty.kind {
if adt.is_enum() {
PatKind::Variant {
adt_def: adt,
substs,
variant_index: self.variant_index_for_adt(cx, adt),
subpatterns,
}
} else {
PatKind::Leaf { subpatterns }
}