rust/src/librustc_data_structures/transitive_relation.rs

598 lines
18 KiB
Rust

// Copyright 2015 The Rust Project Developers. See the COPYRIGHT
// file at the top-level directory of this distribution and at
// http://rust-lang.org/COPYRIGHT.
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
use bitvec::BitMatrix;
use std::cell::RefCell;
use std::fmt::Debug;
use std::mem;
#[derive(Clone)]
pub struct TransitiveRelation<T: Debug + PartialEq> {
// List of elements. This is used to map from a T to a usize. We
// expect domain to be small so just use a linear list versus a
// hashmap or something.
elements: Vec<T>,
// List of base edges in the graph. Require to compute transitive
// closure.
edges: Vec<Edge>,
// This is a cached transitive closure derived from the edges.
// Currently, we build it lazilly and just throw out any existing
// copy whenever a new edge is added. (The RefCell is to permit
// the lazy computation.) This is kind of silly, except for the
// fact its size is tied to `self.elements.len()`, so I wanted to
// wait before building it up to avoid reallocating as new edges
// are added with new elements. Perhaps better would be to ask the
// user for a batch of edges to minimize this effect, but I
// already wrote the code this way. :P -nmatsakis
closure: RefCell<Option<BitMatrix>>,
}
#[derive(Clone, PartialEq, PartialOrd)]
struct Index(usize);
#[derive(Clone, PartialEq)]
struct Edge {
source: Index,
target: Index,
}
impl<T: Debug + PartialEq> TransitiveRelation<T> {
pub fn new() -> TransitiveRelation<T> {
TransitiveRelation {
elements: vec![],
edges: vec![],
closure: RefCell::new(None),
}
}
fn index(&self, a: &T) -> Option<Index> {
self.elements.iter().position(|e| *e == *a).map(Index)
}
fn add_index(&mut self, a: T) -> Index {
match self.index(&a) {
Some(i) => i,
None => {
self.elements.push(a);
// if we changed the dimensions, clear the cache
*self.closure.borrow_mut() = None;
Index(self.elements.len() - 1)
}
}
}
/// Indicate that `a < b` (where `<` is this relation)
pub fn add(&mut self, a: T, b: T) {
let a = self.add_index(a);
let b = self.add_index(b);
let edge = Edge {
source: a,
target: b,
};
if !self.edges.contains(&edge) {
self.edges.push(edge);
// added an edge, clear the cache
*self.closure.borrow_mut() = None;
}
}
/// Check whether `a < target` (transitively)
pub fn contains(&self, a: &T, b: &T) -> bool {
match (self.index(a), self.index(b)) {
(Some(a), Some(b)) => self.with_closure(|closure| closure.contains(a.0, b.0)),
(None, _) | (_, None) => false,
}
}
/// Picks what I am referring to as the "postdominating"
/// upper-bound for `a` and `b`. This is usually the least upper
/// bound, but in cases where there is no single least upper
/// bound, it is the "mutual immediate postdominator", if you
/// imagine a graph where `a < b` means `a -> b`.
///
/// This function is needed because region inference currently
/// requires that we produce a single "UB", and there is no best
/// choice for the LUB. Rather than pick arbitrarily, I pick a
/// less good, but predictable choice. This should help ensure
/// that region inference yields predictable results (though it
/// itself is not fully sufficient).
///
/// Examples are probably clearer than any prose I could write
/// (there are corresponding tests below, btw). In each case,
/// the query is `postdom_upper_bound(a, b)`:
///
/// ```text
/// // returns Some(x), which is also LUB
/// a -> a1 -> x
/// ^
/// |
/// b -> b1 ---+
///
/// // returns Some(x), which is not LUB (there is none)
/// // diagonal edges run left-to-right
/// a -> a1 -> x
/// \/ ^
/// /\ |
/// b -> b1 ---+
///
/// // returns None
/// a -> a1
/// b -> b1
/// ```
pub fn postdom_upper_bound(&self, a: &T, b: &T) -> Option<&T> {
let mut mubs = self.minimal_upper_bounds(a, b);
loop {
match mubs.len() {
0 => return None,
1 => return Some(mubs[0]),
_ => {
let m = mubs.pop().unwrap();
let n = mubs.pop().unwrap();
mubs.extend(self.minimal_upper_bounds(n, m));
}
}
}
}
/// Returns the set of bounds `X` such that:
///
/// - `a < X` and `b < X`
/// - there is no `Y != X` such that `a < Y` and `Y < X`
/// - except for the case where `X < a` (i.e., a strongly connected
/// component in the graph). In that case, the smallest
/// representative of the SCC is returned (as determined by the
/// internal indices).
///
/// Note that this set can, in principle, have any size.
pub fn minimal_upper_bounds(&self, a: &T, b: &T) -> Vec<&T> {
let (mut a, mut b) = match (self.index(a), self.index(b)) {
(Some(a), Some(b)) => (a, b),
(None, _) | (_, None) => {
return vec![];
}
};
// in some cases, there are some arbitrary choices to be made;
// it doesn't really matter what we pick, as long as we pick
// the same thing consistently when queried, so ensure that
// (a, b) are in a consistent relative order
if a > b {
mem::swap(&mut a, &mut b);
}
let lub_indices = self.with_closure(|closure| {
// Easy case is when either a < b or b < a:
if closure.contains(a.0, b.0) {
return vec![b.0];
}
if closure.contains(b.0, a.0) {
return vec![a.0];
}
// Otherwise, the tricky part is that there may be some c
// where a < c and b < c. In fact, there may be many such
// values. So here is what we do:
//
// 1. Find the vector `[X | a < X && b < X]` of all values
// `X` where `a < X` and `b < X`. In terms of the
// graph, this means all values reachable from both `a`
// and `b`. Note that this vector is also a set, but we
// use the term vector because the order matters
// to the steps below.
// - This vector contains upper bounds, but they are
// not minimal upper bounds. So you may have e.g.
// `[x, y, tcx, z]` where `x < tcx` and `y < tcx` and
// `z < x` and `z < y`:
//
// z --+---> x ----+----> tcx
// | |
// | |
// +---> y ----+
//
// In this case, we really want to return just `[z]`.
// The following steps below achieve this by gradually
// reducing the list.
// 2. Pare down the vector using `pare_down`. This will
// remove elements from the vector that can be reached
// by an earlier element.
// - In the example above, this would convert `[x, y,
// tcx, z]` to `[x, y, z]`. Note that `x` and `y` are
// still in the vector; this is because while `z < x`
// (and `z < y`) holds, `z` comes after them in the
// vector.
// 3. Reverse the vector and repeat the pare down process.
// - In the example above, we would reverse to
// `[z, y, x]` and then pare down to `[z]`.
// 4. Reverse once more just so that we yield a vector in
// increasing order of index. Not necessary, but why not.
//
// I believe this algorithm yields a minimal set. The
// argument is that, after step 2, we know that no element
// can reach its successors (in the vector, not the graph).
// After step 3, we know that no element can reach any of
// its predecesssors (because of step 2) nor successors
// (because we just called `pare_down`)
let mut candidates = closure.intersection(a.0, b.0); // (1)
pare_down(&mut candidates, closure); // (2)
candidates.reverse(); // (3a)
pare_down(&mut candidates, closure); // (3b)
candidates
});
lub_indices.into_iter()
.rev() // (4)
.map(|i| &self.elements[i])
.collect()
}
fn with_closure<OP, R>(&self, op: OP) -> R
where OP: FnOnce(&BitMatrix) -> R
{
let mut closure_cell = self.closure.borrow_mut();
let mut closure = closure_cell.take();
if closure.is_none() {
closure = Some(self.compute_closure());
}
let result = op(closure.as_ref().unwrap());
*closure_cell = closure;
result
}
fn compute_closure(&self) -> BitMatrix {
let mut matrix = BitMatrix::new(self.elements.len());
let mut changed = true;
while changed {
changed = false;
for edge in self.edges.iter() {
// add an edge from S -> T
changed |= matrix.add(edge.source.0, edge.target.0);
// add all outgoing edges from T into S
changed |= matrix.merge(edge.target.0, edge.source.0);
}
}
matrix
}
}
/// Pare down is used as a step in the LUB computation. It edits the
/// candidates array in place by removing any element j for which
/// there exists an earlier element i<j such that i -> j. That is,
/// after you run `pare_down`, you know that for all elements that
/// remain in candidates, they cannot reach any of the elements that
/// come after them.
///
/// Examples follow. Assume that a -> b -> c and x -> y -> z.
///
/// - Input: `[a, b, x]`. Output: `[a, x]`.
/// - Input: `[b, a, x]`. Output: `[b, a, x]`.
/// - Input: `[a, x, b, y]`. Output: `[a, x]`.
fn pare_down(candidates: &mut Vec<usize>, closure: &BitMatrix) {
let mut i = 0;
while i < candidates.len() {
let candidate_i = candidates[i];
i += 1;
let mut j = i;
let mut dead = 0;
while j < candidates.len() {
let candidate_j = candidates[j];
if closure.contains(candidate_i, candidate_j) {
// If `i` can reach `j`, then we can remove `j`. So just
// mark it as dead and move on; subsequent indices will be
// shifted into its place.
dead += 1;
} else {
candidates[j - dead] = candidate_j;
}
j += 1;
}
candidates.truncate(j - dead);
}
}
#[test]
fn test_one_step() {
let mut relation = TransitiveRelation::new();
relation.add("a", "b");
relation.add("a", "c");
assert!(relation.contains(&"a", &"c"));
assert!(relation.contains(&"a", &"b"));
assert!(!relation.contains(&"b", &"a"));
assert!(!relation.contains(&"a", &"d"));
}
#[test]
fn test_many_steps() {
let mut relation = TransitiveRelation::new();
relation.add("a", "b");
relation.add("a", "c");
relation.add("a", "f");
relation.add("b", "c");
relation.add("b", "d");
relation.add("b", "e");
relation.add("e", "g");
assert!(relation.contains(&"a", &"b"));
assert!(relation.contains(&"a", &"c"));
assert!(relation.contains(&"a", &"d"));
assert!(relation.contains(&"a", &"e"));
assert!(relation.contains(&"a", &"f"));
assert!(relation.contains(&"a", &"g"));
assert!(relation.contains(&"b", &"g"));
assert!(!relation.contains(&"a", &"x"));
assert!(!relation.contains(&"b", &"f"));
}
#[test]
fn mubs_triange() {
let mut relation = TransitiveRelation::new();
relation.add("a", "tcx");
relation.add("b", "tcx");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"tcx"]);
}
#[test]
fn mubs_best_choice1() {
// 0 -> 1 <- 3
// | ^ |
// | | |
// +--> 2 <--+
//
// mubs(0,3) = [1]
// This tests a particular state in the algorithm, in which we
// need the second pare down call to get the right result (after
// intersection, we have [1, 2], but 2 -> 1).
let mut relation = TransitiveRelation::new();
relation.add("0", "1");
relation.add("0", "2");
relation.add("2", "1");
relation.add("3", "1");
relation.add("3", "2");
assert_eq!(relation.minimal_upper_bounds(&"0", &"3"), vec![&"2"]);
}
#[test]
fn mubs_best_choice2() {
// 0 -> 1 <- 3
// | | |
// | v |
// +--> 2 <--+
//
// mubs(0,3) = [2]
// Like the precedecing test, but in this case intersection is [2,
// 1], and hence we rely on the first pare down call.
let mut relation = TransitiveRelation::new();
relation.add("0", "1");
relation.add("0", "2");
relation.add("1", "2");
relation.add("3", "1");
relation.add("3", "2");
assert_eq!(relation.minimal_upper_bounds(&"0", &"3"), vec![&"1"]);
}
#[test]
fn mubs_no_best_choice() {
// in this case, the intersection yields [1, 2], and the "pare
// down" calls find nothing to remove.
let mut relation = TransitiveRelation::new();
relation.add("0", "1");
relation.add("0", "2");
relation.add("3", "1");
relation.add("3", "2");
assert_eq!(relation.minimal_upper_bounds(&"0", &"3"), vec![&"1", &"2"]);
}
#[test]
fn mubs_best_choice_scc() {
let mut relation = TransitiveRelation::new();
relation.add("0", "1");
relation.add("0", "2");
relation.add("1", "2");
relation.add("2", "1");
relation.add("3", "1");
relation.add("3", "2");
assert_eq!(relation.minimal_upper_bounds(&"0", &"3"), vec![&"1"]);
}
#[test]
fn pdub_crisscross() {
// diagonal edges run left-to-right
// a -> a1 -> x
// \/ ^
// /\ |
// b -> b1 ---+
let mut relation = TransitiveRelation::new();
relation.add("a", "a1");
relation.add("a", "b1");
relation.add("b", "a1");
relation.add("b", "b1");
relation.add("a1", "x");
relation.add("b1", "x");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"),
vec![&"a1", &"b1"]);
assert_eq!(relation.postdom_upper_bound(&"a", &"b"), Some(&"x"));
}
#[test]
fn pdub_crisscross_more() {
// diagonal edges run left-to-right
// a -> a1 -> a2 -> a3 -> x
// \/ \/ ^
// /\ /\ |
// b -> b1 -> b2 ---------+
let mut relation = TransitiveRelation::new();
relation.add("a", "a1");
relation.add("a", "b1");
relation.add("b", "a1");
relation.add("b", "b1");
relation.add("a1", "a2");
relation.add("a1", "b2");
relation.add("b1", "a2");
relation.add("b1", "b2");
relation.add("a2", "a3");
relation.add("a3", "x");
relation.add("b2", "x");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"),
vec![&"a1", &"b1"]);
assert_eq!(relation.minimal_upper_bounds(&"a1", &"b1"),
vec![&"a2", &"b2"]);
assert_eq!(relation.postdom_upper_bound(&"a", &"b"), Some(&"x"));
}
#[test]
fn pdub_lub() {
// a -> a1 -> x
// ^
// |
// b -> b1 ---+
let mut relation = TransitiveRelation::new();
relation.add("a", "a1");
relation.add("b", "b1");
relation.add("a1", "x");
relation.add("b1", "x");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"x"]);
assert_eq!(relation.postdom_upper_bound(&"a", &"b"), Some(&"x"));
}
#[test]
fn mubs_intermediate_node_on_one_side_only() {
// a -> c -> d
// ^
// |
// b
// "digraph { a -> c -> d; b -> d; }",
let mut relation = TransitiveRelation::new();
relation.add("a", "c");
relation.add("c", "d");
relation.add("b", "d");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"d"]);
}
#[test]
fn mubs_scc_1() {
// +-------------+
// | +----+ |
// | v | |
// a -> c -> d <-+
// ^
// |
// b
// "digraph { a -> c -> d; d -> c; a -> d; b -> d; }",
let mut relation = TransitiveRelation::new();
relation.add("a", "c");
relation.add("c", "d");
relation.add("d", "c");
relation.add("a", "d");
relation.add("b", "d");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"c"]);
}
#[test]
fn mubs_scc_2() {
// +----+
// v |
// a -> c -> d
// ^ ^
// | |
// +--- b
// "digraph { a -> c -> d; d -> c; b -> d; b -> c; }",
let mut relation = TransitiveRelation::new();
relation.add("a", "c");
relation.add("c", "d");
relation.add("d", "c");
relation.add("b", "d");
relation.add("b", "c");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"c"]);
}
#[test]
fn mubs_scc_3() {
// +---------+
// v |
// a -> c -> d -> e
// ^ ^
// | |
// b ---+
// "digraph { a -> c -> d -> e -> c; b -> d; b -> e; }",
let mut relation = TransitiveRelation::new();
relation.add("a", "c");
relation.add("c", "d");
relation.add("d", "e");
relation.add("e", "c");
relation.add("b", "d");
relation.add("b", "e");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"c"]);
}
#[test]
fn mubs_scc_4() {
// +---------+
// v |
// a -> c -> d -> e
// | ^ ^
// +---------+ |
// |
// b ---+
// "digraph { a -> c -> d -> e -> c; a -> d; b -> e; }"
let mut relation = TransitiveRelation::new();
relation.add("a", "c");
relation.add("c", "d");
relation.add("d", "e");
relation.add("e", "c");
relation.add("a", "d");
relation.add("b", "e");
assert_eq!(relation.minimal_upper_bounds(&"a", &"b"), vec![&"c"]);
}