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_match.rs
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/// 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_{m + 1})` where `P` is a list of patterns
/// of length `m` for a compound (product) type with `n` components (we refer to this as
/// a matrix). `U(P, p_{m + 1})` represents whether, given an existing list of patterns
/// `p_1 ..= p_m`, adding a new pattern 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).
///
/// For example, say we have the following:
/// ```
/// // x: (Option<bool>, Result<()>)
/// match x {
/// (Some(true), _) => {}
/// (None, Err(())) => {}
/// (None, Err(_)) => {}
/// }
/// ```
/// Here, the matrix `P` is 3 x 2 (rows x columns).
/// [
/// [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.
///
/// To compute `U`, we must have two other concepts.
/// 1. `S(c, P)` is a "specialized matrix", where `c` is a constructor (like `Some` or
/// `None`). You can think of it as filtering `P` to just the rows whose *first* pattern
/// can cover `c` (and expanding OR-patterns into distinct patterns), and then expanding
/// the constructor into all of its components.
/// The specialization of a row vector is computed by `specialize`.
///
/// It is computed as follows. For each row `p_i` of P, we have four cases:
/// 1.1. `p_(i,1) = c(r_1, .., r_a)`. Then `S(c, P)` has a corresponding row:
/// r_1, .., r_a, p_(i,2), .., p_(i,n)
/// 1.2. `p_(i,1) = c'(r_1, .., r_a')` where `c ≠ c'`. Then `S(c, P)` has no
/// corresponding row.
/// 1.3. `p_(i,1) = _`. Then `S(c, P)` has a corresponding row:
/// _, .., _, p_(i,2), .., p_(i,n)
/// 1.4. `p_(i,1) = r_1 | r_2`. Then `S(c, P)` has corresponding rows inlined from:
/// S(c, (r_1, p_(i,2), .., p_(i,n)))
/// S(c, (r_2, p_(i,2), .., p_(i,n)))
///
/// 2. `D(P)` is a "default matrix". 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.
/// The default matrix is computed inline in `is_useful`.
///
/// It is computed as follows. For each row `p_i` of P, we have three cases:
/// 1.1. `p_(i,1) = c(r_1, .., r_a)`. Then `D(P)` has no corresponding row.
/// 1.2. `p_(i,1) = _`. Then `D(P)` has a corresponding row:
/// p_(i,2), .., p_(i,n)
/// 1.3. `p_(i,1) = r_1 | r_2`. Then `D(P)` has corresponding rows inlined from:
/// D((r_1, p_(i,2), .., p_(i,n)))
/// D((r_2, p_(i,2), .., p_(i,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.
///
/// 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 `p_{m + 1}`.
/// 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_{m + 1})` is false.
/// - Otherwise, `P` must be empty, so `U(P, p_{m + 1})` 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 new pattern, `p_{m + 1}`.
/// - If `p_{m + 1} == c(r_1, .., r_a)`, then we have a constructor pattern.
/// Thus, the usefulness of `p_{m + 1}` can be reduced to whether it is useful when
/// we ignore all the patterns in `P` that involve other constructors. This is where
/// `S(c, P)` comes in:
/// `U(P, p_{m + 1}) := U(S(c, P), S(c, p_{m + 1}))`
/// This special case is handled in `is_useful_specialized`.
/// - If `p_{m + 1} == _`, then we have two more cases:
/// + All the constructors of the first component of the type exist within
/// all the rows (after having expanded OR-patterns). In this case:
/// `U(P, p_{m + 1}) := ∨(k ϵ constructors) U(S(k, P), S(k, p_{m + 1}))`
/// I.e., the pattern `p_{m + 1}` is only useful when all the constructors are
/// present *if* its later components are useful for the respective constructors
/// covered by `p_{m + 1}` (usually a single constructor, but all in the case of `_`).
/// + Some constructors are not present in the existing rows (after having expanded
/// OR-patterns). However, there might be wildcard patterns (`_`) present. Thus, we
/// are only really concerned with the other patterns leading with wildcards. This is
/// where `D` comes in:
/// `U(P, p_{m + 1}) := U(D(P), p_({m + 1},2), .., p_({m + 1},n))`
/// - If `p_{m + 1} == r_1 | r_2`, then the usefulness depends on each separately:
/// `U(P, p_{m + 1}) := U(P, (r_1, p_({m + 1},2), .., p_({m + 1},n)))
/// || U(P, (r_2, p_({m + 1},2), .., p_({m + 1},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_{m + 1}` 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::Usefulness::*;
use self::WitnessPreference::*;
use rustc_data_structures::fx::FxHashMap;
use rustc_data_structures::indexed_vec::Idx;
use super::{FieldPattern, Pattern, PatternKind, PatternRange};
use super::{PatternFoldable, PatternFolder, compare_const_vals};
use rustc::hir::def_id::DefId;
use rustc::hir::RangeEnd;
use rustc::ty::{self, Ty, TyCtxt, TypeFoldable, Const};
use rustc::ty::layout::{Integer, IntegerExt, VariantIdx, Size};
use rustc::mir::Field;
use rustc::mir::interpret::{ConstValue, Scalar, truncate, AllocId, Pointer};
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, Ordering, min, max};
use std::fmt;
use std::iter::{FromIterator, IntoIterator};
use std::ops::RangeInclusive;
use std::u128;
use std::convert::TryInto;
pub fn expand_pattern<'a, 'tcx>(cx: &MatchCheckCtxt<'a, 'tcx>, pat: Pattern<'tcx>)
-> &'a Pattern<'tcx>
{
cx.pattern_arena.alloc(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.sty, &rty.sty) {
// 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: &Pattern<'tcx>) -> Pattern<'tcx> {
debug!("fold_pattern {:?} {:?} {:?}", pat, pat.ty.sty, pat.kind);
match (&pat.ty.sty, &*pat.kind) {
(
&ty::Ref(_, rty, _),
&PatternKind::Constant { value: Const {
val,
ty: ty::TyS { sty: ty::Ref(_, crty, _), .. },
} },
) => {
Pattern {
ty: pat.ty,
span: pat.span,
kind: box PatternKind::Deref {
subpattern: Pattern {
ty: rty,
span: pat.span,
kind: box PatternKind::Constant { value: self.tcx.mk_const(Const {
val: self.fold_const_value_deref(*val, rty, crty),
ty: rty,
}) },
}
}
}
}
(_, &PatternKind::Binding { subpattern: Some(ref s), .. }) => {
s.fold_with(self)
}
_ => pat.super_fold_with(self)
}
}
}
impl<'tcx> Pattern<'tcx> {
fn is_wildcard(&self) -> bool {
match *self.kind {
PatternKind::Binding { subpattern: None, .. } | PatternKind::Wild =>
true,
_ => false
}
}
}
/// A 2D matrix. Nx1 matrices are very common, which is why `SmallVec[_; 2]`
/// works well for each row.
pub struct Matrix<'p, 'tcx>(Vec<SmallVec<[&'p Pattern<'tcx>; 2]>>);
impl<'p, 'tcx> Matrix<'p, 'tcx> {
pub fn empty() -> Self {
Matrix(vec![])
}
pub fn push(&mut self, row: SmallVec<[&'p Pattern<'tcx>; 2]>) {
self.0.push(row)
}
}
/// 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<SmallVec<[&'p Pattern<'tcx>; 2]>> for Matrix<'p, 'tcx> {
fn from_iter<T>(iter: T) -> Self
where T: IntoIterator<Item=SmallVec<[&'p Pattern<'tcx>; 2]>>
{
Matrix(iter.into_iter().collect())
}
}
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<Pattern<'tcx>>,
pub byte_array_map: FxHashMap<*const Pattern<'tcx>, Vec<&'a Pattern<'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_non_exhaustive_variant<'p>(&self, pattern: &'p Pattern<'tcx>) -> bool {
match *pattern.kind {
PatternKind::Variant { adt_def, variant_index, .. } => {
let ref variant = adt_def.variants[variant_index];
variant.is_field_list_non_exhaustive()
}
_ => false,
}
}
fn is_non_exhaustive_enum(&self, ty: Ty<'tcx>) -> bool {
match ty.sty {
ty::Adt(adt_def, ..) => adt_def.is_variant_list_non_exhaustive(),
_ => false,
}
}
fn is_local(&self, ty: Ty<'tcx>) -> bool {
match ty.sty {
ty::Adt(adt_def, ..) => adt_def.did.is_local(),
_ => false,
}
}
}
#[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 literal values (`2..=5` and `2..5`).
ConstantRange(u128, u128, Ty<'tcx>, RangeEnd),
/// Array patterns of length n.
Slice(u64),
}
impl<'tcx> Constructor<'tcx> {
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)
}
}
}
#[derive(Clone, Debug)]
pub enum Usefulness<'tcx> {
Useful,
UsefulWithWitness(Vec<Witness<'tcx>>),
NotUseful
}
impl<'tcx> Usefulness<'tcx> {
fn is_useful(&self) -> bool {
match *self {
NotUseful => false,
_ => true
}
}
}
#[derive(Copy, Clone, Debug)]
pub enum WitnessPreference {
ConstructWitness,
LeaveOutWitness
}
#[derive(Copy, Clone, Debug)]
struct PatternContext<'tcx> {
ty: Ty<'tcx>,
max_slice_length: u64,
}
/// 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<Pattern<'tcx>>);
impl<'tcx> Witness<'tcx> {
pub fn single_pattern(&self) -> &Pattern<'tcx> {
assert_eq!(self.0.len(), 1);
&self.0[0]
}
fn push_wild_constructor<'a>(
mut self,
cx: &MatchCheckCtxt<'a, 'tcx>,
ctor: &Constructor<'tcx>,
ty: Ty<'tcx>)
-> Self
{
let sub_pattern_tys = constructor_sub_pattern_tys(cx, ctor, ty);
self.0.extend(sub_pattern_tys.into_iter().map(|ty| {
Pattern {
ty,
span: DUMMY_SP,
kind: box PatternKind::Wild,
}
}));
self.apply_constructor(cx, ctor, ty)
}
/// 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 = constructor_arity(cx, ctor, ty);
let pat = {
let len = self.0.len() as u64;
let mut pats = self.0.drain((len - arity) as usize..).rev();
match ty.sty {
ty::Adt(..) |
ty::Tuple(..) => {
let pats = pats.enumerate().map(|(i, p)| {
FieldPattern {
field: Field::new(i),
pattern: p
}
}).collect();
if let ty::Adt(adt, substs) = ty.sty {
if adt.is_enum() {
PatternKind::Variant {
adt_def: adt,
substs,
variant_index: ctor.variant_index_for_adt(cx, adt),
subpatterns: pats
}
} else {
PatternKind::Leaf { subpatterns: pats }
}
} else {
PatternKind::Leaf { subpatterns: pats }
}
}
ty::Ref(..) => {
PatternKind::Deref { subpattern: pats.nth(0).unwrap() }
}
ty::Slice(_) | ty::Array(..) => {
PatternKind::Slice {
prefix: pats.collect(),
slice: None,
suffix: vec![]
}
}
_ => {
match *ctor {
ConstantValue(value) => PatternKind::Constant { value },
ConstantRange(lo, hi, ty, end) => PatternKind::Range(PatternRange {
lo: ty::Const::from_bits(cx.tcx, lo, ty::ParamEnv::empty().and(ty)),
hi: ty::Const::from_bits(cx.tcx, hi, ty::ParamEnv::empty().and(ty)),
end,
}),
_ => PatternKind::Wild,
}
}
}
};
self.0.push(Pattern {
ty,
span: DUMMY_SP,
kind: Box::new(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: PatternContext<'tcx>,
) -> Vec<Constructor<'tcx>> {
debug!("all_constructors({:?})", pcx.ty);
let ctors = match pcx.ty.sty {
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(len)]
}
}
// Treat arrays of a constant but unknown length like slices.
ty::Array(ref sub_ty, _) |
ty::Slice(ref sub_ty) => {
if cx.is_uninhabited(sub_ty) {
vec![Slice(0)]
} else {
(0..pcx.max_slice_length+1).map(|length| Slice(length)).collect()
}
}
ty::Adt(def, substs) if def.is_enum() => {
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()
}
ty::Char => {
vec![
// The valid Unicode Scalar Value ranges.
ConstantRange('\u{0000}' as u128,
'\u{D7FF}' as u128,
cx.tcx.types.char,
RangeEnd::Included
),
ConstantRange('\u{E000}' as u128,
'\u{10FFFF}' as u128,
cx.tcx.types.char,
RangeEnd::Included
),
]
}
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![ConstantRange(min, max, pcx.ty, RangeEnd::Included)]
}
ty::Uint(uty) => {
let size = Integer::from_attr(&cx.tcx, UnsignedInt(uty)).size();
let max = truncate(u128::max_value(), size);
vec![ConstantRange(0, max, pcx.ty, RangeEnd::Included)]
}
_ => {
if cx.is_uninhabited(pcx.ty) {
vec![]
} else {
vec![Single]
}
}
};
ctors
}
fn max_slice_length<'p, 'a, 'tcx, I>(cx: &mut MatchCheckCtxt<'a, 'tcx>, patterns: I) -> u64
where
I: Iterator<Item = &'p Pattern<'tcx>>,
'tcx: 'p,
{
// 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(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 = 0;
let mut max_suffix_len = 0;
let mut max_fixed_len = 0;
for row in patterns {
match *row.kind {
PatternKind::Constant { value } => {
// extract the length of an array/slice from a constant
match (value.val, &value.ty.sty) {
(_, ty::Array(_, n)) => max_fixed_len = cmp::max(
max_fixed_len,
n.eval_usize(cx.tcx, cx.param_env),
),
(ConstValue::Slice{ start, end, .. }, ty::Slice(_)) => max_fixed_len = cmp::max(
max_fixed_len,
(end - start) as u64,
),
_ => {},
}
}
PatternKind::Slice { ref prefix, slice: None, ref suffix } => {
let fixed_len = prefix.len() as u64 + suffix.len() as u64;
max_fixed_len = cmp::max(max_fixed_len, fixed_len);
}
PatternKind::Slice { ref prefix, slice: Some(_), ref suffix } => {
max_prefix_len = cmp::max(max_prefix_len, prefix.len() as u64);
max_suffix_len = cmp::max(max_suffix_len, suffix.len() as u64);
}
_ => {}
}
}
cmp::max(max_fixed_len + 1, max_prefix_len + max_suffix_len)
}
/// 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)]
struct IntRange<'tcx> {
pub range: RangeInclusive<u128>,
pub ty: Ty<'tcx>,
}
impl<'tcx> IntRange<'tcx> {
fn from_ctor(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
ctor: &Constructor<'tcx>,
) -> Option<IntRange<'tcx>> {
// Floating-point ranges are permitted and we don't want
// to consider them when constructing integer ranges.
fn is_integral(ty: Ty<'_>) -> bool {
match ty.sty {
ty::Char | ty::Int(_) | ty::Uint(_) => true,
_ => false,
}
}
match ctor {
ConstantRange(lo, hi, ty, end) if 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);
// Make sure the interval is well-formed.
if lo > hi || lo == hi && *end == RangeEnd::Excluded {
None
} else {
let offset = (*end == RangeEnd::Excluded) as u128;
Some(IntRange { range: lo..=(hi - offset), ty })
}
}
ConstantValue(val) if is_integral(val.ty) => {
let ty = val.ty;
if let Some(val) = val.try_eval_bits(tcx, param_env, ty) {
let bias = IntRange::signed_bias(tcx, ty);
let val = val ^ bias;
Some(IntRange { range: val..=val, ty })
} else {
None
}
}
_ => None,
}
}
fn from_pat(
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
mut pat: &Pattern<'tcx>,
) -> Option<IntRange<'tcx>> {
let range = loop {
match pat.kind {
box PatternKind::Constant { value } => break ConstantValue(value),
box PatternKind::Range(PatternRange { lo, hi, end }) => break ConstantRange(
lo.eval_bits(tcx, param_env, lo.ty),
hi.eval_bits(tcx, param_env, hi.ty),
lo.ty,
end,
),
box PatternKind::AscribeUserType { ref subpattern, .. } => {
pat = subpattern;
},
_ => return None,
}
};
Self::from_ctor(tcx, param_env, &range)
}
// 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.sty {
ty::Int(ity) => {
let bits = Integer::from_attr(&tcx, SignedInt(ity)).size().bits() as u128;
1u128 << (bits - 1)
}
_ => 0
}
}
/// Converts a `RangeInclusive` to a `ConstantValue` or inclusive `ConstantRange`.
fn range_to_ctor(
tcx: TyCtxt<'tcx>,
ty: Ty<'tcx>,
r: RangeInclusive<u128>,
) -> Constructor<'tcx> {
let bias = IntRange::signed_bias(tcx, ty);
let (lo, hi) = r.into_inner();
if lo == hi {
let ty = ty::ParamEnv::empty().and(ty);
ConstantValue(ty::Const::from_bits(tcx, lo ^ bias, ty))
} else {
ConstantRange(lo ^ bias, hi ^ bias, ty, RangeEnd::Included)
}
}
/// 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,
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,
ranges: Vec<Constructor<'tcx>>,
) -> Vec<Constructor<'tcx>> {
let ranges = ranges.into_iter().filter_map(|r| {
IntRange::from_ctor(tcx, param_env, &r).map(|i| i.range)
});
let mut remaining_ranges = vec![];
let ty = self.ty;
let (lo, hi) = self.range.into_inner();
for subrange in ranges {
let (subrange_lo, subrange_hi) = subrange.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(Self::range_to_ctor(tcx, ty, subrange_lo..=subrange_hi));
} else {
if lo > subrange_lo {
// The pattern intersects an upper section of the
// subrange, so a lower section will remain.
remaining_ranges.push(Self::range_to_ctor(tcx, ty, subrange_lo..=(lo - 1)));
}
if hi < subrange_hi {
// The pattern intersects a lower section of the
// subrange, so an upper section will remain.
remaining_ranges.push(Self::range_to_ctor(tcx, ty, (hi + 1)..=subrange_hi));
}
}
}
remaining_ranges
}
fn intersection(&self, other: &Self) -> Option<Self> {
let ty = self.ty;
let (lo, hi) = (*self.range.start(), *self.range.end());
let (other_lo, other_hi) = (*other.range.start(), *other.range.end());
if lo <= other_hi && other_lo <= hi {
Some(IntRange { range: max(lo, other_lo)..=min(hi, other_hi), ty })
} else {
None
}
}
}
// A request for missing constructor data in terms of either:
// - whether or not there any missing constructors; or
// - the actual set of missing constructors.
#[derive(PartialEq)]
enum MissingCtorsInfo {
Emptiness,
Ctors,
}
// Used by `compute_missing_ctors`.
#[derive(Debug, PartialEq)]
enum MissingCtors<'tcx> {
Empty,
NonEmpty,
// Note that the Vec can be empty.
Ctors(Vec<Constructor<'tcx>>),
}
// When `info` is `MissingCtorsInfo::Ctors`, compute a set of constructors
// equivalent to `all_ctors \ used_ctors`. When `info` is
// `MissingCtorsInfo::Emptiness`, just determines if that set is empty or not.
// (The split logic gives a performance win, because we always need to know if
// the set is empty, but we rarely need the full set, and it can be expensive
// to compute the full set.)
fn compute_missing_ctors<'tcx>(
info: MissingCtorsInfo,
tcx: TyCtxt<'tcx>,
param_env: ty::ParamEnv<'tcx>,