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fuchsia / third_party / rust / 15f159addefd8fea7564ba7617c8af78582b7816 / . / src / librustc_mir / hair / pattern / _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::fx::FxHashMap;
use rustc_index::vec::Idx;
use super::{compare_const_vals, PatternFoldable, PatternFolder};
use super::{FieldPat, Pat, PatKind, PatRange};
use rustc::hir::def_id::DefId;
use rustc::hir::{HirId, RangeEnd};
use rustc::ty::layout::{Integer, IntegerExt, Size, VariantIdx};
use rustc::ty::{self, Const, Ty, TyCtxt, TypeFoldable};
use rustc::lint;
use rustc::mir::interpret::{truncate, AllocId, ConstValue, Pointer, Scalar};
use rustc::mir::Field;
use rustc::util::captures::Captures;
use rustc::util::common::ErrorReported;
use syntax::attr::{SignedInt, UnsignedInt};
use syntax_pos::{Span, DUMMY_SP};
use arena::TypedArena;
use smallvec::{smallvec, SmallVec};
use std::cmp::{self, max, min, Ordering};
use std::convert::TryInto;
use std::fmt;
use std::iter::{FromIterator, IntoIterator};
use std::ops::RangeInclusive;
use std::u128;
pub fn expand_pattern<'a, 'tcx>(cx: &MatchCheckCtxt<'a, 'tcx>, pat: Pat<'tcx>) -> Pat<'tcx> {
LiteralExpander { tcx: cx.tcx }.fold_pattern(&pat)
}
struct LiteralExpander<'tcx> {
tcx: TyCtxt<'tcx>,
}
impl 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(Scalar::Ptr(p)), x, y) if x == y => {
let alloc = self.tcx.alloc_map.lock().unwrap_memory(p.alloc_id);
ConstValue::ByRef { alloc, offset: p.offset }
}
// 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 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: self.tcx.mk_const(Const {
val: ty::ConstKind::Value(
self.fold_const_value_deref(*val, rty, crty),
),
ty: 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> {
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)]
pub struct PatStack<'p, 'tcx>(SmallVec<[&'p Pat<'tcx>; 2]>);
impl<'p, 'tcx> PatStack<'p, 'tcx> {
pub 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().map(|p| *p)
}
// 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<'a, 'q>(
&self,
cx: &mut MatchCheckCtxt<'a, 'tcx>,
constructor: &Constructor<'tcx>,
ctor_wild_subpatterns: &[&'q Pat<'tcx>],
) -> Option<PatStack<'q, 'tcx>>
where
'a: 'q,
'p: 'q,
{
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.
pub struct Matrix<'p, 'tcx>(Vec<PatStack<'p, 'tcx>>);
impl<'p, 'tcx> Matrix<'p, 'tcx> {
pub fn empty() -> Self {
Matrix(vec![])
}
/// Pushes a new row to the matrix. If the row starts with an or-pattern, this expands it.
pub fn push(&mut self, row: PatStack<'p, 'tcx>) {
if let Some(rows) = row.expand_or_pat() {
self.0.extend(rows);
} 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<'a, 'q>(
&self,
cx: &mut MatchCheckCtxt<'a, 'tcx>,
constructor: &Constructor<'tcx>,
ctor_wild_subpatterns: &[&'q Pat<'tcx>],
) -> Matrix<'q, 'tcx>
where
'a: 'q,
'p: 'q,
{
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
}
}
pub struct MatchCheckCtxt<'a, 'tcx> {
pub 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.
pub module: DefId,
param_env: ty::ParamEnv<'tcx>,
pub pattern_arena: &'a TypedArena<Pat<'tcx>>,
pub byte_array_map: FxHashMap<*const Pat<'tcx>, Vec<&'a Pat<'tcx>>>,
}
impl<'a, 'tcx> MatchCheckCtxt<'a, 'tcx> {
pub fn create_and_enter<F, R>(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
module: DefId,
f: F,
) -> R
where
F: for<'b> FnOnce(MatchCheckCtxt<'b, 'tcx>) -> R,
{
let pattern_arena = TypedArena::default();
f(MatchCheckCtxt {
tcx,
param_env,
module,
pattern_arena: &pattern_arena,
byte_array_map: FxHashMap::default(),
})
}
fn is_uninhabited(&self, ty: Ty<'tcx>) -> bool {
if self.tcx.features().exhaustive_patterns {
self.tcx.is_ty_uninhabited_from(self.module, ty)
} else {
false
}
}
fn is_local(&self, ty: Ty<'tcx>) -> bool {
match ty.kind {
ty::Adt(adt_def, ..) => adt_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) => crate::const_eval::const_variant_index(cx.tcx, cx.param_env, c),
_ => 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>> {
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 explicitely 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 =
variant.is_field_list_non_exhaustive() && !cx.is_local(ty);
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 }
}
} else {
PatKind::Leaf { subpatterns }
}
}
ty::Ref(..) => PatKind::Deref { subpattern: subpatterns.nth(0).unwrap() },
ty::Slice(_) | ty::Array(..) => bug!("bad slice pattern {:?} {:?}", self, ty),
_ => PatKind::Wild,
},
Slice(slice) => match slice.pattern_kind() {
FixedLen(_) => {
PatKind::Slice { prefix: subpatterns.collect(), slice: None, suffix: vec![] }
}
VarLen(prefix, _) => {
let mut prefix: Vec<_> = subpatterns.by_ref().take(prefix as usize).collect();
if slice.array_len.is_some() {
// Improves diagnostics a bit: if the type is a known-size array, instead
// of reporting `[x, _, .., _, y]`, we prefer to report `[x, .., y]`.
// This is incorrect if the size is not known, since `[_, ..]` captures
// arrays of lengths `>= 1` whereas `[..]` captures any length.
while !prefix.is_empty() && prefix.last().unwrap().is_wildcard() {
prefix.pop();
}
}
let suffix: Vec<_> = if slice.array_len.is_some() {
// Same as above.
subpatterns.skip_while(Pat::is_wildcard).collect()
} else {
subpatterns.collect()
};
let wild = Pat::wildcard_from_ty(ty);
PatKind::Slice { prefix, slice: Some(wild), suffix }
}
},
&ConstantValue(value) => PatKind::Constant { value },
&FloatRange(lo, hi, end) => PatKind::Range(PatRange { lo, hi, end }),
IntRange(range) => return range.to_pat(cx.tcx),
NonExhaustive => PatKind::Wild,
};
Pat { ty, span: DUMMY_SP, kind: Box::new(pat) }
}
/// Like `apply`, but where all the subpatterns are wildcards `_`.
fn apply_wildcards<'a>(&self, cx: &MatchCheckCtxt<'a, 'tcx>, ty: Ty<'tcx>) -> Pat<'tcx> {
let subpatterns = self.wildcard_subpatterns(cx, ty).into_iter().rev();
self.apply(cx, ty, subpatterns)
}
}
#[derive(Clone, Debug)]
pub enum Usefulness<'tcx> {
Useful,
UsefulWithWitness(Vec<Witness<'tcx>>),
NotUseful,
}
impl<'tcx> Usefulness<'tcx> {
fn new_useful(preference: WitnessPreference) -> Self {
match preference {
ConstructWitness => UsefulWithWitness(vec![Witness(vec![])]),
LeaveOutWitness => Useful,
}
}
fn is_useful(&self) -> bool {
match *self {
NotUseful => false,
_ => true,
}
}
fn apply_constructor(
self,
cx: &MatchCheckCtxt<'_, 'tcx>,
ctor: &Constructor<'tcx>,
ty: Ty<'tcx>,
) -> Self {
match self {
UsefulWithWitness(witnesses) => UsefulWithWitness(
witnesses
.into_iter()
.map(|witness| witness.apply_constructor(cx, &ctor, ty))
.collect(),
),
x => x,
}
}
fn apply_wildcard(self, ty: Ty<'tcx>) -> Self {
match self {
UsefulWithWitness(witnesses) => {
let wild = Pat::wildcard_from_ty(ty);
UsefulWithWitness(
witnesses
.into_iter()
.map(|mut witness| {
witness.0.push(wild.clone());
witness
})
.collect(),
)
}
x => x,
}
}
fn apply_missing_ctors(
self,
cx: &MatchCheckCtxt<'_, 'tcx>,
ty: Ty<'tcx>,
missing_ctors: &MissingConstructors<'tcx>,
) -> Self {
match self {
UsefulWithWitness(witnesses) => {
let new_patterns: Vec<_> =
missing_ctors.iter().map(|ctor| ctor.apply_wildcards(cx, ty)).collect();
// Add the new patterns to each witness
UsefulWithWitness(
witnesses
.into_iter()
.flat_map(|witness| {
new_patterns.iter().map(move |pat| {
let mut witness = witness.clone();
witness.0.push(pat.clone());
witness
})
})
.collect(),
)
}
x => x,
}
}
}
#[derive(Copy, Clone, Debug)]
pub enum WitnessPreference {
ConstructWitness,
LeaveOutWitness,
}
#[derive(Copy, Clone, Debug)]
struct PatCtxt<'tcx> {
ty: Ty<'tcx>,
span: Span,
}
/// A witness of non-exhaustiveness for error reporting, represented
/// as a list of patterns (in reverse order of construction) with
/// wildcards inside to represent elements that can take any inhabitant
/// of the type as a value.
///
/// A witness against a list of patterns should have the same types
/// and length as the pattern matched against. Because Rust `match`
/// is always against a single pattern, at the end the witness will
/// have length 1, but in the middle of the algorithm, it can contain
/// multiple patterns.
///
/// For example, if we are constructing a witness for the match against
/// ```
/// struct Pair(Option<(u32, u32)>, bool);
///
/// match (p: Pair) {
/// Pair(None, _) => {}
/// Pair(_, false) => {}
/// }
/// ```
///
/// We'll perform the following steps:
/// 1. Start with an empty witness
/// `Witness(vec![])`
/// 2. Push a witness `Some(_)` against the `None`
/// `Witness(vec![Some(_)])`
/// 3. Push a witness `true` against the `false`
/// `Witness(vec![Some(_), true])`
/// 4. Apply the `Pair` constructor to the witnesses
/// `Witness(vec![Pair(Some(_), true)])`
///
/// The final `Pair(Some(_), true)` is then the resulting witness.
#[derive(Clone, Debug)]
pub struct Witness<'tcx>(Vec<Pat<'tcx>>);
impl<'tcx> Witness<'tcx> {
pub fn single_pattern(self) -> Pat<'tcx> {
assert_eq!(self.0.len(), 1);
self.0.into_iter().next().unwrap()
}
/// Constructs a partial witness for a pattern given a list of
/// patterns expanded by the specialization step.
///
/// When a pattern P is discovered to be useful, this function is used bottom-up
/// to reconstruct a complete witness, e.g., a pattern P' that covers a subset
/// of values, V, where each value in that set is not covered by any previously
/// used patterns and is covered by the pattern P'. Examples:
///
/// left_ty: tuple of 3 elements
/// pats: [10, 20, _] => (10, 20, _)
///
/// left_ty: struct X { a: (bool, &'static str), b: usize}
/// pats: [(false, "foo"), 42] => X { a: (false, "foo"), b: 42 }
fn apply_constructor<'a>(
mut self,
cx: &MatchCheckCtxt<'a, 'tcx>,
ctor: &Constructor<'tcx>,
ty: Ty<'tcx>,
) -> Self {
let arity = ctor.arity(cx, ty);
let pat = {
let len = self.0.len() as u64;
let pats = self.0.drain((len - arity) as usize..).rev();
ctor.apply(cx, ty, pats)
};
self.0.push(pat);
self
}
}
/// This determines the set of all possible constructors of a pattern matching
/// values of type `left_ty`. For vectors, this would normally be an infinite set
/// but is instead bounded by the maximum fixed length of slice patterns in
/// the column of patterns being analyzed.
///
/// We make sure to omit constructors that are statically impossible. E.g., for
/// `Option<!>`, we do not include `Some(_)` in the returned list of constructors.
fn all_constructors<'a, 'tcx>(
cx: &mut MatchCheckCtxt<'a, 'tcx>,
pcx: PatCtxt<'tcx>,
) -> Vec<Constructor<'tcx>> {
debug!("all_constructors({:?})", pcx.ty);
let make_range = |start, end| {
IntRange(
// `unwrap()` is ok because we know the type is an integer.
IntRange::from_range(cx.tcx, start, end, pcx.ty, &RangeEnd::Included, pcx.span)
.unwrap(),
)
};
match pcx.ty.kind {
ty::Bool => {
[true, false].iter().map(|&b| ConstantValue(ty::Const::from_bool(cx.tcx, b))).collect()
}
ty::Array(ref sub_ty, len) if len.try_eval_usize(cx.tcx, cx.param_env).is_some() => {
let len = len.eval_usize(cx.tcx, cx.param_env);
if len != 0 && cx.is_uninhabited(sub_ty) {
vec![]
} else {
vec![Slice(Slice { array_len: Some(len), kind: VarLen(0, 0) })]
}
}
// Treat arrays of a constant but unknown length like slices.
ty::Array(ref sub_ty, _) | ty::Slice(ref sub_ty) => {
let kind = if cx.is_uninhabited(sub_ty) { FixedLen(0) } else { VarLen(0, 0) };
vec![Slice(Slice { array_len: None, kind })]
}
ty::Adt(def, substs) if def.is_enum() => {
let ctors: Vec<_> = def
.variants
.iter()
.filter(|v| {
!cx.tcx.features().exhaustive_patterns
|| !v
.uninhabited_from(cx.tcx, substs, def.adt_kind())
.contains(cx.tcx, cx.module)
})
.map(|v| Variant(v.def_id))
.collect();
// If our scrutinee is *privately* an empty enum, we must treat it as though it had an
// "unknown" constructor (in that case, all other patterns obviously can't be variants)
// to avoid exposing its emptyness. See the `match_privately_empty` test for details.
// FIXME: currently the only way I know of something can be a privately-empty enum is
// when the exhaustive_patterns feature flag is not present, so this is only needed for
// that case.
let is_privately_empty = ctors.is_empty() && !cx.is_uninhabited(pcx.ty);
// If the enum is declared as `#[non_exhaustive]`, we treat it as if it had an
// additionnal "unknown" constructor.
let is_declared_nonexhaustive =
def.is_variant_list_non_exhaustive() && !cx.is_local(pcx.ty);
if is_privately_empty || is_declared_nonexhaustive {
// There is no point in enumerating all possible variants, because the user can't
// actually match against them themselves. So we return only the fictitious
// constructor.
// E.g., in an example like:
// ```
// let err: io::ErrorKind = ...;
// match err {
// io::ErrorKind::NotFound => {},
// }
// ```
// we don't want to show every possible IO error, but instead have only `_` as the
// witness.
vec![NonExhaustive]
} else {
ctors
}
}
ty::Char => {
vec![
// The valid Unicode Scalar Value ranges.
make_range('\u{0000}' as u128, '\u{D7FF}' as u128),
make_range('\u{E000}' as u128, '\u{10FFFF}' as u128),
]
}
ty::Int(_) | ty::Uint(_)
if pcx.ty.is_ptr_sized_integral()
&& !cx.tcx.features().precise_pointer_size_matching =>
{
// `usize`/`isize` are not allowed to be matched exhaustively unless the
// `precise_pointer_size_matching` feature is enabled. So we treat those types like
// `#[non_exhaustive]` enums by returning a special unmatcheable constructor.
vec![NonExhaustive]
}
ty::Int(ity) => {
let bits = Integer::from_attr(&cx.tcx, SignedInt(ity)).size().bits() as u128;
let min = 1u128 << (bits - 1);
let max = min - 1;
vec![make_range(min, max)]
}
ty::Uint(uty) => {
let size = Integer::from_attr(&cx.tcx, UnsignedInt(uty)).size();
let max = truncate(u128::max_value(), size);
vec![make_range(0, max)]
}
_ => {
if cx.is_uninhabited(pcx.ty) {
vec![]
} else {
vec![Single]
}
}
}
}
/// An inclusive interval, used for precise integer exhaustiveness checking.
/// `IntRange`s always store a contiguous range. This means that values are
/// encoded such that `0` encodes the minimum value for the integer,
/// regardless of the signedness.
/// For example, the pattern `-128..=127i8` is encoded as `0..=255`.
/// This makes comparisons and arithmetic on interval endpoints much more
/// straightforward. See `signed_bias` for details.
///
/// `IntRange` is never used to encode an empty range or a "range" that wraps
/// around the (offset) space: i.e., `range.lo <= range.hi`.
#[derive(Clone, Debug)]
struct IntRange<'tcx> {
pub range: RangeInclusive<u128>,
pub ty: Ty<'tcx>,
pub span: Span,
}
impl<'tcx> IntRange<'tcx> {
#[inline]
fn is_integral(ty: Ty<'_>) -> bool {
match ty.kind {
ty::Char | ty::Int(_) | ty::Uint(_) => true,
_ => false,
}
}
fn is_singleton(&self) -> bool {
self.range.start() == self.range.end()
}
fn boundaries(&self) -> (u128, u128) {
(*self.range.start(), *self.range.end())
}
/// Don't treat `usize`/`isize` exhaustively unless the `precise_pointer_size_matching` feature
/// is enabled.
fn treat_exhaustively(&self, tcx: TyCtxt<'tcx>) -> bool {
!self.ty.is_ptr_sized_integral() || tcx.features().precise_pointer_size_matching
}
#[inline]
fn integral_size_and_signed_bias(tcx: TyCtxt<'tcx>, ty: Ty<'_>) -> Option<(Size, u128)> {
match ty.kind {
ty::Char => Some((Size::from_bytes(4), 0)),
ty::Int(ity) => {
let size = Integer::from_attr(&tcx, SignedInt(ity)).size();
Some((size, 1u128 << (size.bits() as u128 - 1)))
}
ty::Uint(uty) => Some((Integer::from_attr(&tcx, UnsignedInt(uty)).size(), 0)),
_ => None,
}
}
#[inline]
fn from_const(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
value: &Const<'tcx>,
span: Span,
) -> Option<IntRange<'tcx>> {
if let Some((target_size, bias)) = Self::integral_size_and_signed_bias(tcx, value.ty) {
let ty = value.ty;
let val = if let ty::ConstKind::Value(ConstValue::Scalar(Scalar::Raw { data, size })) =
value.val
{
// For this specific pattern we can skip a lot of effort and go
// straight to the result, after doing a bit of checking. (We
// could remove this branch and just use the next branch, which
// is more general but much slower.)
Scalar::<()>::check_raw(data, size, target_size);
data
} else if let Some(val) = value.try_eval_bits(tcx, param_env, ty) {
// This is a more general form of the previous branch.
val
} else {
return None;
};
let val = val ^ bias;
Some(IntRange { range: val..=val, ty, span })
} else {
None
}
}
#[inline]
fn from_range(
tcx: TyCtxt<'tcx>,
lo: u128,
hi: u128,
ty: Ty<'tcx>,
end: &RangeEnd,
span: Span,
) -> Option<IntRange<'tcx>> {
if Self::is_integral(ty) {
// Perform a shift if the underlying types are signed,
// which makes the interval arithmetic simpler.
let bias = IntRange::signed_bias(tcx, ty);
let (lo, hi) = (lo ^ bias, hi ^ bias);
let offset = (*end == RangeEnd::Excluded) as u128;
if lo > hi || (lo == hi && *end == RangeEnd::Excluded) {
// This should have been caught earlier by E0030.
bug!("malformed range pattern: {}..={}", lo, (hi - offset));
}
Some(IntRange { range: lo..=(hi - offset), ty, span })
} else {
None
}
}
fn from_pat(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
pat: &Pat<'tcx>,
) -> Option<IntRange<'tcx>> {
match pat_constructor(tcx, param_env, pat)? {
IntRange(range) => Some(range),
_ => None,
}
}
// The return value of `signed_bias` should be XORed with an endpoint to encode/decode it.
fn signed_bias(tcx: TyCtxt<'tcx>, ty: Ty<'tcx>) -> u128 {
match ty.kind {
ty::Int(ity) => {
let bits = Integer::from_attr(&tcx, SignedInt(ity)).size().bits() as u128;
1u128 << (bits - 1)
}
_ => 0,
}
}
/// Returns a collection of ranges that spans the values covered by `ranges`, subtracted
/// by the values covered by `self`: i.e., `ranges \ self` (in set notation).
fn subtract_from(&self, ranges: Vec<IntRange<'tcx>>) -> Vec<IntRange<'tcx>> {
let mut remaining_ranges = vec![];
let ty = self.ty;
let span = self.span;
let (lo, hi) = self.boundaries();
for subrange in ranges {
let (subrange_lo, subrange_hi) = subrange.range.into_inner();
if lo > subrange_hi || subrange_lo > hi {
// The pattern doesn't intersect with the subrange at all,
// so the subrange remains untouched.
remaining_ranges.push(IntRange { range: subrange_lo..=subrange_hi, ty, span });
} else {
if lo > subrange_lo {
// The pattern intersects an upper section of the
// subrange, so a lower section will remain.
remaining_ranges.push(IntRange { range: subrange_lo..=(lo - 1), ty, span });
}
if hi < subrange_hi {
// The pattern intersects a lower section of the
// subrange, so an upper section will remain.
remaining_ranges.push(IntRange { range: (hi + 1)..=subrange_hi, ty, span });
}
}
}
remaining_ranges
}
fn is_subrange(&self, other: &Self) -> bool {
other.range.start() <= self.range.start() && self.range.end() <= other.range.end()
}
fn intersection(&self, tcx: TyCtxt<'tcx>, other: &Self) -> Option<Self> {
let ty = self.ty;
let (lo, hi) = self.boundaries();
let (other_lo, other_hi) = other.boundaries();
if self.treat_exhaustively(tcx) {
if lo <= other_hi && other_lo <= hi {
let span = other.span;
Some(IntRange { range: max(lo, other_lo)..=min(hi, other_hi), ty, span })
} else {
None
}
} else {
// If the range should not be treated exhaustively, fallback to checking for inclusion.
if self.is_subrange(other) { Some(self.clone()) } else { None }
}
}
fn suspicious_intersection(&self, other: &Self) -> bool {
// `false` in the following cases:
// 1 ---- // 1 ---------- // 1 ---- // 1 ----
// 2 ---------- // 2 ---- // 2 ---- // 2 ----
//
// The following are currently `false`, but could be `true` in the future (#64007):
// 1 --------- // 1 ---------
// 2 ---------- // 2 ----------
//
// `true` in the following cases:
// 1 ------- // 1 -------
// 2 -------- // 2 -------
let (lo, hi) = self.boundaries();
let (other_lo, other_hi) = other.boundaries();
(lo == other_hi || hi == other_lo)
}
fn to_pat(&self, tcx: TyCtxt<'tcx>) -> Pat<'tcx> {
let (lo, hi) = self.boundaries();
let bias = IntRange::signed_bias(tcx, self.ty);
let (lo, hi) = (lo ^ bias, hi ^ bias);
let ty = ty::ParamEnv::empty().and(self.ty);
let lo_const = ty::Const::from_bits(tcx, lo, ty);
let hi_const = ty::Const::from_bits(tcx, hi, ty);
let kind = if lo == hi {
PatKind::Constant { value: lo_const }
} else {
PatKind::Range(PatRange { lo: lo_const, hi: hi_const, end: RangeEnd::Included })
};
// This is a brand new pattern, so we don't reuse `self.span`.
Pat { ty: self.ty, span: DUMMY_SP, kind: Box::new(kind) }
}
}
/// Ignore spans when comparing, they don't carry semantic information as they are only for lints.
impl<'tcx> std::cmp::PartialEq for IntRange<'tcx> {
fn eq(&self, other: &Self) -> bool {
self.range == other.range && self.ty == other.ty
}
}
// A struct to compute a set of constructors equivalent to `all_ctors \ used_ctors`.
struct MissingConstructors<'tcx> {
all_ctors: Vec<Constructor<'tcx>>,
used_ctors: Vec<Constructor<'tcx>>,
}
impl<'tcx> MissingConstructors<'tcx> {
fn new(all_ctors: Vec<Constructor<'tcx>>, used_ctors: Vec<Constructor<'tcx>>) -> Self {
MissingConstructors { all_ctors, used_ctors }
}
fn into_inner(self) -> (Vec<Constructor<'tcx>>, Vec<Constructor<'tcx>>) {
(self.all_ctors, self.used_ctors)
}
fn is_empty(&self) -> bool {
self.iter().next().is_none()
}
/// Whether this contains all the constructors for the given type or only a
/// subset.
fn all_ctors_are_missing(&self) -> bool {
self.used_ctors.is_empty()
}
/// Iterate over all_ctors \ used_ctors
fn iter<'a>(&'a self) -> impl Iterator<Item = Constructor<'tcx>> + Captures<'a> {
self.all_ctors.iter().flat_map(move |req_ctor| req_ctor.subtract_ctors(&self.used_ctors))
}
}
impl<'tcx> fmt::Debug for MissingConstructors<'tcx> {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
let ctors: Vec<_> = self.iter().collect();
write!(f, "{:?}", ctors)
}
}
/// Algorithm from http://moscova.inria.fr/~maranget/papers/warn/index.html.
/// The algorithm from the paper has been modified to correctly handle empty
/// types. The changes are:
/// (0) We don't exit early if the pattern matrix has zero rows. We just
/// continue to recurse over columns.
/// (1) all_constructors will only return constructors that are statically
/// possible. E.g., it will only return `Ok` for `Result<T, !>`.
///
/// This finds whether a (row) vector `v` of patterns is 'useful' in relation
/// to a set of such vectors `m` - this is defined as there being a set of
/// inputs that will match `v` but not any of the sets in `m`.
///
/// All the patterns at each column of the `matrix ++ v` matrix must
/// have the same type, except that wildcard (PatKind::Wild) patterns
/// with type `TyErr` are also allowed, even if the "type of the column"
/// is not `TyErr`. That is used to represent private fields, as using their
/// real type would assert that they are inhabited.
///
/// This is used both for reachability checking (if a pattern isn't useful in
/// relation to preceding patterns, it is not reachable) and exhaustiveness
/// checking (if a wildcard pattern is useful in relation to a matrix, the
/// matrix isn't exhaustive).
pub fn is_useful<'p, 'a, 'tcx>(
cx: &mut MatchCheckCtxt<'a, 'tcx>,
matrix: &Matrix<'p, 'tcx>,
v: &PatStack<'_, 'tcx>,
witness_preference: WitnessPreference,
hir_id: HirId,
) -> Usefulness<'tcx> {
let &Matrix(ref rows) = matrix;
debug!("is_useful({:#?}, {:#?})", matrix, v);
// The base case. We are pattern-matching on () and the return value is
// based on whether our matrix has a row or not.
// NOTE: This could potentially be optimized by checking rows.is_empty()
// first and then, if v is non-empty, the return value is based on whether
// the type of the tuple we're checking is inhabited or not.
if v.is_empty() {
return if rows.is_empty() {
Usefulness::new_useful(witness_preference)
} else {
NotUseful
};
};
assert!(rows.iter().all(|r| r.len() == v.len()));
// If the first pattern is an or-pattern, expand it.
if let Some(vs) = v.expand_or_pat() {
return vs
.into_iter()
.map(|v| is_useful(cx, matrix, &v, witness_preference, hir_id))
.find(|result| result.is_useful())
.unwrap_or(NotUseful);
}
let (ty, span) = matrix
.heads()
.map(|r| (r.ty, r.span))
.find(|(ty, _)| !ty.references_error())
.unwrap_or((v.head().ty, v.head().span));
let pcx = PatCtxt {
// TyErr is used to represent the type of wildcard patterns matching
// against inaccessible (private) fields of structs, so that we won't
// be able to observe whether the types of the struct's fields are
// inhabited.
//
// If the field is truly inaccessible, then all the patterns
// matching against it must be wildcard patterns, so its type
// does not matter.
//
// However, if we are matching against non-wildcard patterns, we
// need to know the real type of the field so we can specialize
// against it. This primarily occurs through constants - they
// can include contents for fields that are inaccessible at the
// location of the match. In that case, the field's type is
// inhabited - by the constant - so we can just use it.
//
// FIXME: this might lead to "unstable" behavior with macro hygiene
// introducing uninhabited patterns for inaccessible fields. We
// need to figure out how to model that.
ty,
span,
};
debug!("is_useful_expand_first_col: pcx={:#?}, expanding {:#?}", pcx, v.head());
if let Some(constructor) = pat_constructor(cx.tcx, cx.param_env, v.head()) {
debug!("is_useful - expanding constructor: {:#?}", constructor);
split_grouped_constructors(
cx.tcx,
cx.param_env,
pcx,
vec![constructor],
matrix,
pcx.span,
Some(hir_id),
)
.into_iter()
.map(|c| is_useful_specialized(cx, matrix, v, c, pcx.ty, witness_preference, hir_id))
.find(|result| result.is_useful())
.unwrap_or(NotUseful)
} else {
debug!("is_useful - expanding wildcard");
let used_ctors: Vec<Constructor<'_>> =
matrix.heads().filter_map(|p| pat_constructor(cx.tcx, cx.param_env, p)).collect();
debug!("used_ctors = {:#?}", used_ctors);
// `all_ctors` are all the constructors for the given type, which
// should all be represented (or caught with the wild pattern `_`).
let all_ctors = all_constructors(cx, pcx);
debug!("all_ctors = {:#?}", all_ctors);
// `missing_ctors` is the set of constructors from the same type as the
// first column of `matrix` that are matched only by wildcard patterns
// from the first column.
//
// Therefore, if there is some pattern that is unmatched by `matrix`,
// it will still be unmatched if the first constructor is replaced by
// any of the constructors in `missing_ctors`
// Missing constructors are those that are not matched by any non-wildcard patterns in the
// current column. We only fully construct them on-demand, because they're rarely used and
// can be big.
let missing_ctors = MissingConstructors::new(all_ctors, used_ctors);
debug!("missing_ctors.empty()={:#?}", missing_ctors.is_empty(),);
if missing_ctors.is_empty() {
let (all_ctors, _) = missing_ctors.into_inner();
split_grouped_constructors(cx.tcx, cx.param_env, pcx, all_ctors, matrix, DUMMY_SP, None)
.into_iter()
.map(|c| {
is_useful_specialized(cx, matrix, v, c, pcx.ty, witness_preference, hir_id)
})
.find(|result| result.is_useful())
.unwrap_or(NotUseful)
} else {
let matrix = matrix.specialize_wildcard();
let v = v.to_tail();
let usefulness = is_useful(cx, &matrix, &v, witness_preference, hir_id);
// In this case, there's at least one "free"
// constructor that is only matched against by
// wildcard patterns.
//
// There are 2 ways we can report a witness here.
// Commonly, we can report all the "free"
// constructors as witnesses, e.g., if we have:
//
// ```
// enum Direction { N, S, E, W }
// let Direction::N = ...;
// ```
//
// we can report 3 witnesses: `S`, `E`, and `W`.
//
// However, there is a case where we don't want
// to do this and instead report a single `_` witness:
// if the user didn't actually specify a constructor
// in this arm, e.g., in
// ```
// let x: (Direction, Direction, bool) = ...;
// let (_, _, false) = x;
// ```
// we don't want to show all 16 possible witnesses
// `(<direction-1>, <direction-2>, true)` - we are
// satisfied with `(_, _, true)`. In this case,
// `used_ctors` is empty.
if missing_ctors.all_ctors_are_missing() {
// All constructors are unused. Add a wild pattern
// rather than each individual constructor.
usefulness.apply_wildcard(pcx.ty)
} else {
// Construct for each missing constructor a "wild" version of this
// constructor, that matches everything that can be built with
// it. For example, if `ctor` is a `Constructor::Variant` for
// `Option::Some`, we get the pattern `Some(_)`.
usefulness.apply_missing_ctors(cx, pcx.ty, &missing_ctors)
}
}
}
}
/// A shorthand for the `U(S(c, P), S(c, q))` operation from the paper. I.e., `is_useful` applied
/// to the specialised version of both the pattern matrix `P` and the new pattern `q`.
fn is_useful_specialized<'p, 'a, 'tcx>(
cx: &mut MatchCheckCtxt<'a, 'tcx>,
matrix: &Matrix<'p, 'tcx>,
v: &PatStack<'_, 'tcx>,
ctor: Constructor<'tcx>,
lty: Ty<'tcx>,
witness_preference: WitnessPreference,
hir_id: HirId,
) -> Usefulness<'tcx> {
debug!("is_useful_specialized({:#?}, {:#?}, {:?})", v, ctor, lty);
let ctor_wild_subpatterns_owned: Vec<_> = ctor.wildcard_subpatterns(cx, lty);
let ctor_wild_subpatterns: Vec<_> = ctor_wild_subpatterns_owned.iter().collect();
let matrix = matrix.specialize_constructor(cx, &ctor, &ctor_wild_subpatterns);
v.specialize_constructor(cx, &ctor, &ctor_wild_subpatterns)
.map(|v| is_useful(cx, &matrix, &v, witness_preference, hir_id))
.map(|u| u.apply_constructor(cx, &ctor, lty))
.unwrap_or(NotUseful)
}
/// Determines the constructor that the given pattern can be specialized to.
/// Returns `None` in case of a catch-all, which can't be specialized.
fn pat_constructor<'tcx>(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
pat: &Pat<'tcx>,
) -> Option<Constructor<'tcx>> {
match *pat.kind {
PatKind::AscribeUserType { .. } => bug!(), // Handled by `expand_pattern`
PatKind::Binding { .. } | PatKind::Wild => None,
PatKind::Leaf { .. } | PatKind::Deref { .. } => Some(Single),
PatKind::Variant { adt_def, variant_index, .. } => {
Some(Variant(adt_def.variants[variant_index].def_id))
}
PatKind::Constant { value } => {
if let Some(int_range) = IntRange::from_const(tcx, param_env, value, pat.span) {
Some(IntRange(int_range))
} else {
match (value.val, &value.ty.kind) {
(_, ty::Array(_, n)) => {
let len = n.eval_usize(tcx, param_env);
Some(Slice(Slice { array_len: Some(len), kind: FixedLen(len) }))
}
(ty::ConstKind::Value(ConstValue::Slice { start, end, .. }), ty::Slice(_)) => {
let len = (end - start) as u64;
Some(Slice(Slice { array_len: None, kind: FixedLen(len) }))
}
// FIXME(oli-obk): implement `deref` for `ConstValue`
// (ty::ConstKind::Value(ConstValue::ByRef { .. }), ty::Slice(_)) => { ... }
_ => Some(ConstantValue(value)),
}
}
}
PatKind::Range(PatRange { lo, hi, end }) => {
let ty = lo.ty;
if let Some(int_range) = IntRange::from_range(
tcx,
lo.eval_bits(tcx, param_env, lo.ty),
hi.eval_bits(tcx, param_env, hi.ty),
ty,
&end,
pat.span,
) {
Some(IntRange(int_range))
} else {
Some(FloatRange(lo, hi, end))
}
}
PatKind::Array { ref prefix, ref slice, ref suffix }
| PatKind::Slice { ref prefix, ref slice, ref suffix } => {
let array_len = match pat.ty.kind {
ty::Array(_, length) => Some(length.eval_usize(tcx, param_env)),
ty::Slice(_) => None,
_ => span_bug!(pat.span, "bad ty {:?} for slice pattern", pat.ty),
};
let prefix = prefix.len() as u64;
let suffix = suffix.len() as u64;
let kind =
if slice.is_some() { VarLen(prefix, suffix) } else { FixedLen(prefix + suffix) };
Some(Slice(Slice { array_len, kind }))
}
PatKind::Or { .. } => bug!("Or-pattern should have been expanded earlier on."),
}
}
// checks whether a constant is equal to a user-written slice pattern. Only supports byte slices,
// meaning all other types will compare unequal and thus equal patterns often do not cause the
// second pattern to lint about unreachable match arms.
fn slice_pat_covered_by_const<'tcx>(
tcx: TyCtxt<'tcx>,
_span: Span,
const_val: &'tcx ty::Const<'tcx>,
prefix: &[Pat<'tcx>],
slice: &Option<Pat<'tcx>>,
suffix: &[Pat<'tcx>],
param_env: ty::ParamEnv<'tcx>,
) -> Result<bool, ErrorReported> {
let const_val_val = if let ty::ConstKind::Value(val) = const_val.val {
val
} else {
bug!(
"slice_pat_covered_by_const: {:#?}, {:#?}, {:#?}, {:#?}",
const_val,
prefix,
slice,
suffix,
)
};
let data: &[u8] = match (const_val_val, &const_val.ty.kind) {
(ConstValue::ByRef { offset, alloc, .. }, ty::Array(t, n)) => {
assert_eq!(*t, tcx.types.u8);
let n = n.eval_usize(tcx, param_env);
let ptr = Pointer::new(AllocId(0), offset);
alloc.get_bytes(&tcx, ptr, Size::from_bytes(n)).unwrap()
}
(ConstValue::Slice { data, start, end }, ty::Slice(t)) => {
assert_eq!(*t, tcx.types.u8);
let ptr = Pointer::new(AllocId(0), Size::from_bytes(start as u64));
data.get_bytes(&tcx, ptr, Size::from_bytes((end - start) as u64)).unwrap()
}
// FIXME(oli-obk): create a way to extract fat pointers from ByRef
(_, ty::Slice(_)) => return Ok(false),
_ => bug!(
"slice_pat_covered_by_const: {:#?}, {:#?}, {:#?}, {:#?}",
const_val,
prefix,
slice,
suffix,
),
};
let pat_len = prefix.len() + suffix.len();
if data.len() < pat_len || (slice.is_none() && data.len() > pat_len) {
return Ok(false);
}
for (ch, pat) in data[..prefix.len()]
.iter()
.zip(prefix)
.chain(data[data.len() - suffix.len()..].iter().zip(suffix))
{
match pat.kind {
box PatKind::Constant { value } => {
let b = value.eval_bits(tcx, param_env, pat.ty);
assert_eq!(b as u8 as u128, b);
if b as u8 != *ch {
return Ok(false);
}
}
_ => {}
}
}
Ok(true)
}
/// For exhaustive integer matching, some constructors are grouped within other constructors
/// (namely integer typed values are grouped within ranges). However, when specialising these
/// constructors, we want to be specialising for the underlying constructors (the integers), not
/// the groups (the ranges). Thus we need to split the groups up. Splitting them up naïvely would
/// mean creating a separate constructor for every single value in the range, which is clearly
/// impractical. However, observe that for some ranges of integers, the specialisation will be
/// identical across all values in that range (i.e., there are equivalence classes of ranges of
/// constructors based on their `is_useful_specialized` outcome). These classes are grouped by
/// the patterns that apply to them (in the matrix `P`). We can split the range whenever the
/// patterns that apply to that range (specifically: the patterns that *intersect* with that range)
/// change.
/// Our solution, therefore, is to split the range constructor into subranges at every single point
/// the group of intersecting patterns changes (using the method described below).
/// And voilà! We're testing precisely those ranges that we need to, without any exhaustive matching
/// on actual integers. The nice thing about this is that the number of subranges is linear in the
/// number of rows in the matrix (i.e., the number of cases in the `match` statement), so we don't
/// need to be worried about matching over gargantuan ranges.
///
/// Essentially, given the first column of a matrix representing ranges, looking like the following:
///
/// |------| |----------| |-------| ||
/// |-------| |-------| |----| ||
/// |---------|
///
/// We split the ranges up into equivalence classes so the ranges are no longer overlapping:
///
/// |--|--|||-||||--||---|||-------| |-|||| ||
///
/// The logic for determining how to split the ranges is fairly straightforward: we calculate
/// boundaries for each interval range, sort them, then create constructors for each new interval
/// between every pair of boundary points. (This essentially sums up to performing the intuitive
/// merging operation depicted above.)
///
/// `hir_id` is `None` when we're evaluating the wildcard pattern, do not lint for overlapping in
/// ranges that case.
///
/// This also splits variable-length slices into fixed-length slices.
fn split_grouped_constructors<'p, 'tcx>(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
pcx: PatCtxt<'tcx>,
ctors: Vec<Constructor<'tcx>>,
matrix: &Matrix<'p, 'tcx>,
span: Span,
hir_id: Option<HirId>,
) -> Vec<Constructor<'tcx>> {
let ty = pcx.ty;
let mut split_ctors = Vec::with_capacity(ctors.len());
debug!("split_grouped_constructors({:#?}, {:#?})", matrix, ctors);
for ctor in ctors.into_iter() {
match ctor {
IntRange(ctor_range) if ctor_range.treat_exhaustively(tcx) => {
// Fast-track if the range is trivial. In particular, don't do the overlapping
// ranges check.
if ctor_range.is_singleton() {
split_ctors.push(IntRange(ctor_range));
continue;
}
/// Represents a border between 2 integers. Because the intervals spanning borders
/// must be able to cover every integer, we need to be able to represent
/// 2^128 + 1 such borders.
#[derive(Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Debug)]
enum Border {
JustBefore(u128),
AfterMax,
}
// A function for extracting the borders of an integer interval.
fn range_borders(r: IntRange<'_>) -> impl Iterator<Item = Border> {
let (lo, hi) = r.range.into_inner();
let from = Border::JustBefore(lo);
let to = match hi.checked_add(1) {
Some(m) => Border::JustBefore(m),
None => Border::AfterMax,
};
vec![from, to].into_iter()
}
// Collect the span and range of all the intersecting ranges to lint on likely
// incorrect range patterns. (#63987)
let mut overlaps = vec![];
// `borders` is the set of borders between equivalence classes: each equivalence
// class lies between 2 borders.
let row_borders = matrix
.0
.iter()
.flat_map(|row| {
IntRange::from_pat(tcx, param_env, row.head()).map(|r| (r, row.len()))
})
.flat_map(|(range, row_len)| {
let intersection = ctor_range.intersection(tcx, &range);
let should_lint = ctor_range.suspicious_intersection(&range);
if let (Some(range), 1, true) = (&intersection, row_len, should_lint) {
// FIXME: for now, only check for overlapping ranges on simple range
// patterns. Otherwise with the current logic the following is detected
// as overlapping:
// match (10u8, true) {
// (0 ..= 125, false) => {}
// (126 ..= 255, false) => {}
// (0 ..= 255, true) => {}
// }
overlaps.push(range.clone());
}
intersection
})
.flat_map(|range| range_borders(range));
let ctor_borders = range_borders(ctor_range.clone());
let mut borders: Vec<_> = row_borders.chain(ctor_borders).collect();
borders.sort_unstable();
lint_overlapping_patterns(tcx, hir_id, ctor_range, ty, overlaps);
// We're going to iterate through every adjacent pair of borders, making sure that
// each represents an interval of nonnegative length, and convert each such
// interval into a constructor.
split_ctors.extend(
borders
.windows(2)
.filter_map(|window| match (window[0], window[1]) {
(Border::JustBefore(n), Border::JustBefore(m)) => {
if n < m {
Some(IntRange { range: n..=(m - 1), ty, span })
} else {
None
}
}
(Border::JustBefore(n), Border::AfterMax) => {
Some(IntRange { range: n..=u128::MAX, ty, span })
}
(Border::AfterMax, _) => None,
})
.map(IntRange),
);
}
Slice(Slice { array_len, kind: VarLen(self_prefix, self_suffix) }) => {
// The exhaustiveness-checking paper does not include any details on
// checking variable-length slice patterns. However, they are matched
// by an infinite collection of fixed-length array patterns.
//
// Checking the infinite set directly would take an infinite amount
// of time. However, it turns out that for each finite set of
// patterns `P`, all sufficiently large array lengths are equivalent:
//
// Each slice `s` with a "sufficiently-large" length `l ≥ L` that applies
// to exactly the subset `Pₜ` of `P` can be transformed to a slice
// `sₘ` for each sufficiently-large length `m` that applies to exactly
// the same subset of `P`.
//
// Because of that, each witness for reachability-checking from one
// of the sufficiently-large lengths can be transformed to an
// equally-valid witness from any other length, so we only have
// to check slice lengths from the "minimal sufficiently-large length"
// and below.
//
// Note that the fact that there is a *single* `sₘ` for each `m`
// not depending on the specific pattern in `P` is important: if
// you look at the pair of patterns
// `[true, ..]`
// `[.., false]`
// Then any slice of length ≥1 that matches one of these two
// patterns can be trivially turned to a slice of any
// other length ≥1 that matches them and vice-versa - for
// but the slice from length 2 `[false, true]` that matches neither
// of these patterns can't be turned to a slice from length 1 that
// matches neither of these patterns, so we have to consider
// slices from length 2 there.
//
// Now, to see that that length exists and find it, observe that slice
// patterns are either "fixed-length" patterns (`[_, _, _]`) or
// "variable-length" patterns (`[_, .., _]`).
//
// For fixed-length patterns, all slices with lengths *longer* than
// the pattern's length have the same outcome (of not matching), so
// as long as `L` is greater than the pattern's length we can pick
// any `sₘ` from that length and get the same result.
//
// For variable-length patterns, the situation is more complicated,
// because as seen above the precise value of `sₘ` matters.
//
// However, for each variable-length pattern `p` with a prefix of length
// `plₚ` and suffix of length `slₚ`, only the first `plₚ` and the last
// `slₚ` elements are examined.
//
// Therefore, as long as `L` is positive (to avoid concerns about empty
// types), all elements after the maximum prefix length and before
// the maximum suffix length are not examined by any variable-length
// pattern, and therefore can be added/removed without affecting
// them - creating equivalent patterns from any sufficiently-large
// length.
//
// Of course, if fixed-length patterns exist, we must be sure
// that our length is large enough to miss them all, so
// we can pick `L = max(max(FIXED_LEN)+1, max(PREFIX_LEN) + max(SUFFIX_LEN))`
//
// for example, with the above pair of patterns, all elements
// but the first and last can be added/removed, so any
// witness of length ≥2 (say, `[false, false, true]`) can be
// turned to a witness from any other length ≥2.
let mut max_prefix_len = self_prefix;
let mut max_suffix_len = self_suffix;
let mut max_fixed_len = 0;
let head_ctors =
matrix.heads().filter_map(|pat| pat_constructor(tcx, param_env, pat));
for ctor in head_ctors {
match ctor {
Slice(slice) => match slice.pattern_kind() {
FixedLen(len) => {
max_fixed_len = cmp::max(max_fixed_len, len);
}
VarLen(prefix, suffix) => {
max_prefix_len = cmp::max(max_prefix_len, prefix);
max_suffix_len = cmp::max(max_suffix_len, suffix);
}
},
_ => {}
}
}
// For diagnostics, we keep the prefix and suffix lengths separate, so in the case
// where `max_fixed_len + 1` is the largest, we adapt `max_prefix_len` accordingly,
// so that `L = max_prefix_len + max_suffix_len`.
if max_fixed_len + 1 >= max_prefix_len + max_suffix_len {
// The subtraction can't overflow thanks to the above check.
// The new `max_prefix_len` is also guaranteed to be larger than its previous
// value.
max_prefix_len = max_fixed_len + 1 - max_suffix_len;
}
match array_len {
Some(len) => {
let kind = if max_prefix_len + max_suffix_len < len {
VarLen(max_prefix_len, max_suffix_len)
} else {
FixedLen(len)
};
split_ctors.push(Slice(Slice { array_len, kind }));
}
None => {
// `ctor` originally covered the range `(self_prefix +
// self_suffix..infinity)`. We now split it into two: lengths smaller than
// `max_prefix_len + max_suffix_len` are treated independently as
// fixed-lengths slices, and lengths above are captured by a final VarLen
// constructor.
split_ctors.extend(
(self_prefix + self_suffix..max_prefix_len + max_suffix_len)
.map(|len| Slice(Slice { array_len, kind: FixedLen(len) })),
);
split_ctors.push(Slice(Slice {
array_len,
kind: VarLen(max_prefix_len, max_suffix_len),
}));
}
}
}
// Any other constructor can be used unchanged.
_ => split_ctors.push(ctor),
}
}
debug!("split_grouped_constructors(..)={:#?}", split_ctors);
split_ctors
}
fn lint_overlapping_patterns(
tcx: TyCtxt<'tcx>,
hir_id: Option<HirId>,
ctor_range: IntRange<'tcx>,
ty: Ty<'tcx>,
overlaps: Vec<IntRange<'tcx>>,
) {
if let (true, Some(hir_id)) = (!overlaps.is_empty(), hir_id) {
let mut err = tcx.struct_span_lint_hir(
lint::builtin::OVERLAPPING_PATTERNS,
hir_id,
ctor_range.span,
"multiple patterns covering the same range",
);
err.span_label(ctor_range.span, "overlapping patterns");
for int_range in overlaps {
// Use the real type for user display of the ranges:
err.span_label(
int_range.span,
&format!(
"this range overlaps on `{}`",
IntRange { range: int_range.range, ty, span: DUMMY_SP }.to_pat(tcx),
),
);
}
err.emit();
}
}
fn constructor_covered_by_range<'tcx>(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
ctor: &Constructor<'tcx>,
pat: &Pat<'tcx>,
) -> Option<()> {
if let Single = ctor {
return Some(());
}
let (pat_from, pat_to, pat_end, ty) = match *pat.kind {
PatKind::Constant { value } => (value, value, RangeEnd::Included, value.ty),
PatKind::Range(PatRange { lo, hi, end }) => (lo, hi, end, lo.ty),
_ => bug!("`constructor_covered_by_range` called with {:?}", pat),
};
let (ctor_from, ctor_to, ctor_end) = match *ctor {
ConstantValue(value) => (value, value, RangeEnd::Included),
FloatRange(from, to, ctor_end) => (from, to, ctor_end),
_ => bug!("`constructor_covered_by_range` called with {:?}", ctor),
};
trace!("constructor_covered_by_range {:#?}, {:#?}, {:#?}, {}", ctor, pat_from, pat_to, ty);
let to = compare_const_vals(tcx, ctor_to, pat_to, param_env, ty)?;
let from = compare_const_vals(tcx, ctor_from, pat_from, param_env, ty)?;
let intersects = (from == Ordering::Greater || from == Ordering::Equal)
&& (to == Ordering::Less || (pat_end == ctor_end && to == Ordering::Equal));
if intersects { Some(()) } else { None }
}
fn patterns_for_variant<'p, 'a: 'p, 'tcx>(
cx: &mut MatchCheckCtxt<'a, 'tcx>,
subpatterns: &'p [FieldPat<'tcx>],
ctor_wild_subpatterns: &[&'p Pat<'tcx>],
is_non_exhaustive: bool,
) -> PatStack<'p, 'tcx> {
let mut result = SmallVec::from_slice(ctor_wild_subpatterns);
for subpat in subpatterns {
if !is_non_exhaustive || !cx.is_uninhabited(subpat.pattern.ty) {
result[subpat.field.index()] = &subpat.pattern;
}
}
debug!(
"patterns_for_variant({:#?}, {:#?}) = {:#?}",
subpatterns, ctor_wild_subpatterns, result
);
PatStack::from_vec(result)
}
/// This is the main specialization step. It expands the pattern
/// into `arity` patterns based on the constructor. For most patterns, the step is trivial,
/// for instance tuple patterns are flattened and box patterns expand into their inner pattern.
/// Returns `None` if the pattern does not have the given constructor.
///
/// OTOH, slice patterns with a subslice pattern (tail @ ..) can be expanded into multiple
/// different patterns.
/// Structure patterns with a partial wild pattern (Foo { a: 42, .. }) have their missing
/// fields filled with wild patterns.
fn specialize_one_pattern<'p, 'a: 'p, 'q: 'p, 'tcx>(
cx: &mut MatchCheckCtxt<'a, 'tcx>,
pat: &'q Pat<'tcx>,
constructor: &Constructor<'tcx>,
ctor_wild_subpatterns: &[&'p Pat<'tcx>],
) -> Option<PatStack<'p, 'tcx>> {
if let NonExhaustive = constructor {
// Only a wildcard pattern can match the special extra constructor
return if pat.is_wildcard() { Some(PatStack::default()) } else { None };
}
let result = match *pat.kind {
PatKind::AscribeUserType { .. } => bug!(), // Handled by `expand_pattern`
PatKind::Binding { .. } | PatKind::Wild => {
Some(PatStack::from_slice(ctor_wild_subpatterns))
}
PatKind::Variant { adt_def, variant_index, ref subpatterns, .. } => {
let ref variant = adt_def.variants[variant_index];
let is_non_exhaustive = variant.is_field_list_non_exhaustive() && !cx.is_local(pat.ty);
Some(Variant(variant.def_id))
.filter(|variant_constructor| variant_constructor == constructor)
.map(|_| {
patterns_for_variant(cx, subpatterns, ctor_wild_subpatterns, is_non_exhaustive)
})
}
PatKind::Leaf { ref subpatterns } => {
Some(patterns_for_variant(cx, subpatterns, ctor_wild_subpatterns, false))
}
PatKind::Deref { ref subpattern } => Some(PatStack::from_pattern(subpattern)),
PatKind::Constant { value } if constructor.is_slice() => {
// We extract an `Option` for the pointer because slices of zero
// elements don't necessarily point to memory, they are usually
// just integers. The only time they should be pointing to memory
// is when they are subslices of nonzero slices.
let (alloc, offset, n, ty) = match value.ty.kind {
ty::Array(t, n) => match value.val {
ty::ConstKind::Value(ConstValue::ByRef { offset, alloc, .. }) => {
(alloc, offset, n.eval_usize(cx.tcx, cx.param_env), t)
}
_ => span_bug!(pat.span, "array pattern is {:?}", value,),
},
ty::Slice(t) => {
match value.val {
ty::ConstKind::Value(ConstValue::Slice { data, start, end }) => {
(data, Size::from_bytes(start as u64), (end - start) as u64, t)
}
ty::ConstKind::Value(ConstValue::ByRef { .. }) => {
// FIXME(oli-obk): implement `deref` for `ConstValue`
return None;
}
_ => span_bug!(
pat.span,
"slice pattern constant must be scalar pair but is {:?}",
value,
),
}
}
_ => span_bug!(
pat.span,
"unexpected const-val {:?} with ctor {:?}",
value,
constructor,
),
};
if ctor_wild_subpatterns.len() as u64 == n {
// convert a constant slice/array pattern to a list of patterns.
let layout = cx.tcx.layout_of(cx.param_env.and(ty)).ok()?;
let ptr = Pointer::new(AllocId(0), offset);
(0..n)
.map(|i| {
let ptr = ptr.offset(layout.size * i, &cx.tcx).ok()?;
let scalar = alloc.read_scalar(&cx.tcx, ptr, layout.size).ok()?;
let scalar = scalar.not_undef().ok()?;
let value = ty::Const::from_scalar(cx.tcx, scalar, ty);
let pattern =
Pat { ty, span: pat.span, kind: box PatKind::Constant { value } };
Some(&*cx.pattern_arena.alloc(pattern))
})
.collect()
} else {
None
}
}
PatKind::Constant { .. } | PatKind::Range { .. } => {
// If the constructor is a:
// - Single value: add a row if the pattern contains the constructor.
// - Range: add a row if the constructor intersects the pattern.
if let IntRange(ctor) = constructor {
match IntRange::from_pat(cx.tcx, cx.param_env, pat) {
Some(pat) => ctor.intersection(cx.tcx, &pat).map(|_| {
// Constructor splitting should ensure that all intersections we encounter
// are actually inclusions.
assert!(ctor.is_subrange(&pat));
PatStack::default()
}),
_ => None,
}
} else {
// Fallback for non-ranges and ranges that involve
// floating-point numbers, which are not conveniently handled
// by `IntRange`. For these cases, the constructor may not be a
// range so intersection actually devolves into being covered
// by the pattern.
constructor_covered_by_range(cx.tcx, cx.param_env, constructor, pat)
.map(|()| PatStack::default())
}
}
PatKind::Array { ref prefix, ref slice, ref suffix }
| PatKind::Slice { ref prefix, ref slice, ref suffix } => match *constructor {
Slice(_) => {
let pat_len = prefix.len() + suffix.len();
if let Some(slice_count) = ctor_wild_subpatterns.len().checked_sub(pat_len) {
if slice_count == 0 || slice.is_some() {
Some(
prefix
.iter()
.chain(
ctor_wild_subpatterns
.iter()
.map(|p| *p)
.skip(prefix.len())
.take(slice_count)
.chain(suffix.iter()),
)
.collect(),
)
} else {
None
}
} else {
None
}
}
ConstantValue(cv) => {
match slice_pat_covered_by_const(
cx.tcx,
pat.span,
cv,
prefix,
slice,
suffix,
cx.param_env,
) {
Ok(true) => Some(PatStack::default()),
Ok(false) => None,
Err(ErrorReported) => None,
}
}
_ => span_bug!(pat.span, "unexpected ctor {:?} for slice pat", constructor),
},
PatKind::Or { .. } => bug!("Or-pattern should have been expanded earlier on."),
};
debug!("specialize({:#?}, {:#?}) = {:#?}", pat, ctor_wild_subpatterns, result);
result
}