rustc_data_structures/graph/dominators/mod.rs
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453
//! Finding the dominators in a control-flow graph.
//!
//! Algorithm based on Loukas Georgiadis,
//! "Linear-Time Algorithms for Dominators and Related Problems",
//! <https://www.cs.princeton.edu/techreports/2005/737.pdf>
//!
//! Additionally useful is the original Lengauer-Tarjan paper on this subject,
//! "A Fast Algorithm for Finding Dominators in a Flowgraph"
//! Thomas Lengauer and Robert Endre Tarjan.
//! <https://www.cs.princeton.edu/courses/archive/spr03/cs423/download/dominators.pdf>
use rustc_index::{Idx, IndexSlice, IndexVec};
use super::ControlFlowGraph;
#[cfg(test)]
mod tests;
struct PreOrderFrame<Iter> {
pre_order_idx: PreorderIndex,
iter: Iter,
}
rustc_index::newtype_index! {
#[orderable]
struct PreorderIndex {}
}
#[derive(Clone, Debug)]
pub struct Dominators<Node: Idx> {
kind: Kind<Node>,
}
#[derive(Clone, Debug)]
enum Kind<Node: Idx> {
/// A representation optimized for a small path graphs.
Path,
General(Inner<Node>),
}
pub fn dominators<G: ControlFlowGraph>(g: &G) -> Dominators<G::Node> {
// We often encounter MIR bodies with 1 or 2 basic blocks. Special case the dominators
// computation and representation for those cases.
if is_small_path_graph(g) {
Dominators { kind: Kind::Path }
} else {
Dominators { kind: Kind::General(dominators_impl(g)) }
}
}
fn is_small_path_graph<G: ControlFlowGraph>(g: &G) -> bool {
if g.start_node().index() != 0 {
return false;
}
if g.num_nodes() == 1 {
return true;
}
if g.num_nodes() == 2 {
return g.successors(g.start_node()).any(|n| n.index() == 1);
}
false
}
fn dominators_impl<G: ControlFlowGraph>(graph: &G) -> Inner<G::Node> {
// We allocate capacity for the full set of nodes, because most of the time
// most of the nodes *are* reachable.
let mut parent: IndexVec<PreorderIndex, PreorderIndex> =
IndexVec::with_capacity(graph.num_nodes());
let mut stack = vec![PreOrderFrame {
pre_order_idx: PreorderIndex::ZERO,
iter: graph.successors(graph.start_node()),
}];
let mut pre_order_to_real: IndexVec<PreorderIndex, G::Node> =
IndexVec::with_capacity(graph.num_nodes());
let mut real_to_pre_order: IndexVec<G::Node, Option<PreorderIndex>> =
IndexVec::from_elem_n(None, graph.num_nodes());
pre_order_to_real.push(graph.start_node());
parent.push(PreorderIndex::ZERO); // the parent of the root node is the root for now.
real_to_pre_order[graph.start_node()] = Some(PreorderIndex::ZERO);
// Traverse the graph, collecting a number of things:
//
// * Preorder mapping (to it, and back to the actual ordering)
// * Parents for each vertex in the preorder tree
//
// These are all done here rather than through one of the 'standard'
// graph traversals to help make this fast.
'recurse: while let Some(frame) = stack.last_mut() {
for successor in frame.iter.by_ref() {
if real_to_pre_order[successor].is_none() {
let pre_order_idx = pre_order_to_real.push(successor);
real_to_pre_order[successor] = Some(pre_order_idx);
parent.push(frame.pre_order_idx);
stack.push(PreOrderFrame { pre_order_idx, iter: graph.successors(successor) });
continue 'recurse;
}
}
stack.pop();
}
let reachable_vertices = pre_order_to_real.len();
let mut idom = IndexVec::from_elem_n(PreorderIndex::ZERO, reachable_vertices);
let mut semi = IndexVec::from_fn_n(std::convert::identity, reachable_vertices);
let mut label = semi.clone();
let mut bucket = IndexVec::from_elem_n(vec![], reachable_vertices);
let mut lastlinked = None;
// We loop over vertices in reverse preorder. This implements the pseudocode
// of the simple Lengauer-Tarjan algorithm. A few key facts are noted here
// which are helpful for understanding the code (full proofs and such are
// found in various papers, including one cited at the top of this file).
//
// For each vertex w (which is not the root),
// * semi[w] is a proper ancestor of the vertex w (i.e., semi[w] != w)
// * idom[w] is an ancestor of semi[w] (i.e., idom[w] may equal semi[w])
//
// An immediate dominator of w (idom[w]) is a vertex v where v dominates w
// and every other dominator of w dominates v. (Every vertex except the root has
// a unique immediate dominator.)
//
// A semidominator for a given vertex w (semi[w]) is the vertex v with minimum
// preorder number such that there exists a path from v to w in which all elements (other than w) have
// preorder numbers greater than w (i.e., this path is not the tree path to
// w).
for w in (PreorderIndex::new(1)..PreorderIndex::new(reachable_vertices)).rev() {
// Optimization: process buckets just once, at the start of the
// iteration. Do not explicitly empty the bucket (even though it will
// not be used again), to save some instructions.
//
// The bucket here contains the vertices whose semidominator is the
// vertex w, which we are guaranteed to have found: all vertices who can
// be semidominated by w must have a preorder number exceeding w, so
// they have been placed in the bucket.
//
// We compute a partial set of immediate dominators here.
for &v in bucket[w].iter() {
// This uses the result of Lemma 5 from section 2 from the original
// 1979 paper, to compute either the immediate or relative dominator
// for a given vertex v.
//
// eval returns a vertex y, for which semi[y] is minimum among
// vertices semi[v] +> y *> v. Note that semi[v] = w as we're in the
// w bucket.
//
// Given such a vertex y, semi[y] <= semi[v] and idom[y] = idom[v].
// If semi[y] = semi[v], though, idom[v] = semi[v].
//
// Using this, we can either set idom[v] to be:
// * semi[v] (i.e. w), if semi[y] is w
// * idom[y], otherwise
//
// We don't directly set to idom[y] though as it's not necessarily
// known yet. The second preorder traversal will cleanup by updating
// the idom for any that were missed in this pass.
let y = eval(&mut parent, lastlinked, &semi, &mut label, v);
idom[v] = if semi[y] < w { y } else { w };
}
// This loop computes the semi[w] for w.
semi[w] = w;
for v in graph.predecessors(pre_order_to_real[w]) {
// TL;DR: Reachable vertices may have unreachable predecessors, so ignore any of them.
//
// Ignore blocks which are not connected to the entry block.
//
// The algorithm that was used to traverse the graph and build the
// `pre_order_to_real` and `real_to_pre_order` vectors does so by
// starting from the entry block and following the successors.
// Therefore, any blocks not reachable from the entry block will be
// set to `None` in the `pre_order_to_real` vector.
//
// For example, in this graph, A and B should be skipped:
//
// ┌─────┐
// │ │
// └──┬──┘
// │
// ┌──▼──┐ ┌─────┐
// │ │ │ A │
// └──┬──┘ └──┬──┘
// │ │
// ┌───────┴───────┐ │
// │ │ │
// ┌──▼──┐ ┌──▼──┐ ┌──▼──┐
// │ │ │ │ │ B │
// └──┬──┘ └──┬──┘ └──┬──┘
// │ └──────┬─────┘
// ┌──▼──┐ │
// │ │ │
// └──┬──┘ ┌──▼──┐
// │ │ │
// │ └─────┘
// ┌──▼──┐
// │ │
// └──┬──┘
// │
// ┌──▼──┐
// │ │
// └─────┘
//
// ...this may be the case if a MirPass modifies the CFG to remove
// or rearrange certain blocks/edges.
let Some(v) = real_to_pre_order[v] else { continue };
// eval returns a vertex x from which semi[x] is minimum among
// vertices semi[v] +> x *> v.
//
// From Lemma 4 from section 2, we know that the semidominator of a
// vertex w is the minimum (by preorder number) vertex of the
// following:
//
// * direct predecessors of w with preorder number less than w
// * semidominators of u such that u > w and there exists (v, w)
// such that u *> v
//
// This loop therefore identifies such a minima. Note that any
// semidominator path to w must have all but the first vertex go
// through vertices numbered greater than w, so the reverse preorder
// traversal we are using guarantees that all of the information we
// might need is available at this point.
//
// The eval call will give us semi[x], which is either:
//
// * v itself, if v has not yet been processed
// * A possible 'best' semidominator for w.
let x = eval(&mut parent, lastlinked, &semi, &mut label, v);
semi[w] = std::cmp::min(semi[w], semi[x]);
}
// semi[w] is now semidominator(w) and won't change any more.
// Optimization: Do not insert into buckets if parent[w] = semi[w], as
// we then immediately know the idom.
//
// If we don't yet know the idom directly, then push this vertex into
// our semidominator's bucket, where it will get processed at a later
// stage to compute its immediate dominator.
let z = parent[w];
if z != semi[w] {
bucket[semi[w]].push(w);
} else {
idom[w] = z;
}
// Optimization: We share the parent array between processed and not
// processed elements; lastlinked represents the divider.
lastlinked = Some(w);
}
// Finalize the idoms for any that were not fully settable during initial
// traversal.
//
// If idom[w] != semi[w] then we know that we've stored vertex y from above
// into idom[w]. It is known to be our 'relative dominator', which means
// that it's one of w's ancestors and has the same immediate dominator as w,
// so use that idom.
for w in PreorderIndex::new(1)..PreorderIndex::new(reachable_vertices) {
if idom[w] != semi[w] {
idom[w] = idom[idom[w]];
}
}
let mut immediate_dominators = IndexVec::from_elem_n(None, graph.num_nodes());
for (idx, node) in pre_order_to_real.iter_enumerated() {
immediate_dominators[*node] = Some(pre_order_to_real[idom[idx]]);
}
let start_node = graph.start_node();
immediate_dominators[start_node] = None;
let time = compute_access_time(start_node, &immediate_dominators);
Inner { immediate_dominators, time }
}
/// Evaluate the link-eval virtual forest, providing the currently minimum semi
/// value for the passed `node` (which may be itself).
///
/// This maintains that for every vertex v, `label[v]` is such that:
///
/// ```text
/// semi[eval(v)] = min { semi[label[u]] | root_in_forest(v) +> u *> v }
/// ```
///
/// where `+>` is a proper ancestor and `*>` is just an ancestor.
#[inline]
fn eval(
ancestor: &mut IndexSlice<PreorderIndex, PreorderIndex>,
lastlinked: Option<PreorderIndex>,
semi: &IndexSlice<PreorderIndex, PreorderIndex>,
label: &mut IndexSlice<PreorderIndex, PreorderIndex>,
node: PreorderIndex,
) -> PreorderIndex {
if is_processed(node, lastlinked) {
compress(ancestor, lastlinked, semi, label, node);
label[node]
} else {
node
}
}
#[inline]
fn is_processed(v: PreorderIndex, lastlinked: Option<PreorderIndex>) -> bool {
if let Some(ll) = lastlinked { v >= ll } else { false }
}
#[inline]
fn compress(
ancestor: &mut IndexSlice<PreorderIndex, PreorderIndex>,
lastlinked: Option<PreorderIndex>,
semi: &IndexSlice<PreorderIndex, PreorderIndex>,
label: &mut IndexSlice<PreorderIndex, PreorderIndex>,
v: PreorderIndex,
) {
assert!(is_processed(v, lastlinked));
// Compute the processed list of ancestors
//
// We use a heap stack here to avoid recursing too deeply, exhausting the
// stack space.
let mut stack: smallvec::SmallVec<[_; 8]> = smallvec::smallvec![v];
let mut u = ancestor[v];
while is_processed(u, lastlinked) {
stack.push(u);
u = ancestor[u];
}
// Then in reverse order, popping the stack
for &[v, u] in stack.array_windows().rev() {
if semi[label[u]] < semi[label[v]] {
label[v] = label[u];
}
ancestor[v] = ancestor[u];
}
}
/// Tracks the list of dominators for each node.
#[derive(Clone, Debug)]
struct Inner<N: Idx> {
// Even though we track only the immediate dominator of each node, it's
// possible to get its full list of dominators by looking up the dominator
// of each dominator.
immediate_dominators: IndexVec<N, Option<N>>,
time: IndexVec<N, Time>,
}
impl<Node: Idx> Dominators<Node> {
/// Returns true if node is reachable from the start node.
pub fn is_reachable(&self, node: Node) -> bool {
match &self.kind {
Kind::Path => true,
Kind::General(g) => g.time[node].start != 0,
}
}
/// Returns the immediate dominator of node, if any.
pub fn immediate_dominator(&self, node: Node) -> Option<Node> {
match &self.kind {
Kind::Path => {
if 0 < node.index() {
Some(Node::new(node.index() - 1))
} else {
None
}
}
Kind::General(g) => g.immediate_dominators[node],
}
}
/// Returns true if `a` dominates `b`.
///
/// # Panics
///
/// Panics if `b` is unreachable.
#[inline]
pub fn dominates(&self, a: Node, b: Node) -> bool {
match &self.kind {
Kind::Path => a.index() <= b.index(),
Kind::General(g) => {
let a = g.time[a];
let b = g.time[b];
assert!(b.start != 0, "node {b:?} is not reachable");
a.start <= b.start && b.finish <= a.finish
}
}
}
}
/// Describes the number of vertices discovered at the time when processing of a particular vertex
/// started and when it finished. Both values are zero for unreachable vertices.
#[derive(Copy, Clone, Default, Debug)]
struct Time {
start: u32,
finish: u32,
}
fn compute_access_time<N: Idx>(
start_node: N,
immediate_dominators: &IndexSlice<N, Option<N>>,
) -> IndexVec<N, Time> {
// Transpose the dominator tree edges, so that child nodes of vertex v are stored in
// node[edges[v].start..edges[v].end].
let mut edges: IndexVec<N, std::ops::Range<u32>> =
IndexVec::from_elem(0..0, immediate_dominators);
for &idom in immediate_dominators.iter() {
if let Some(idom) = idom {
edges[idom].end += 1;
}
}
let mut m = 0;
for e in edges.iter_mut() {
m += e.end;
e.start = m;
e.end = m;
}
let mut node = IndexVec::from_elem_n(Idx::new(0), m.try_into().unwrap());
for (i, &idom) in immediate_dominators.iter_enumerated() {
if let Some(idom) = idom {
edges[idom].start -= 1;
node[edges[idom].start] = i;
}
}
// Perform a depth-first search of the dominator tree. Record the number of vertices discovered
// when vertex v is discovered first as time[v].start, and when its processing is finished as
// time[v].finish.
let mut time: IndexVec<N, Time> = IndexVec::from_elem(Time::default(), immediate_dominators);
let mut stack = Vec::new();
let mut discovered = 1;
stack.push(start_node);
time[start_node].start = discovered;
while let Some(&i) = stack.last() {
let e = &mut edges[i];
if e.start == e.end {
// Finish processing vertex i.
time[i].finish = discovered;
stack.pop();
} else {
let j = node[e.start];
e.start += 1;
// Start processing vertex j.
discovered += 1;
time[j].start = discovered;
stack.push(j);
}
}
time
}