src/main/java/com/google/devtools/build/lib/graph/Digraph.java

// Copyright 2014 The Bazel Authors. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//    http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package com.google.devtools.build.lib.graph;

import static java.util.Comparator.comparing;
import static java.util.Comparator.comparingLong;

import com.google.common.base.Preconditions;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableSet;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.PriorityQueue;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;
import javax.annotation.Nullable;

/**
 * {@code Digraph} a generic directed graph or "digraph", suitable for modeling asymmetric binary
 * relations.
 *
 * <p>An instance <code>G = &lt;V,E&gt;</code> consists of a set of nodes or vertices <code>V</code>
 * , and a set of directed edges <code>E</code>, which is a subset of <code>V &times; V</code>. This
 * permits self-edges but does not represent multiple edges between the same pair of nodes.
 *
 * <p>Nodes may be labeled with values of any type (type parameter T). All nodes within a graph have
 * distinct labels. The null pointer is not a valid label.
 *
 * <p>The package supports various operations for modeling partial order relations, and supports
 * input/output in AT&amp;T's 'dot' format. See http://www.research.att.com/sw/tools/graphviz/.
 *
 * <p>Some invariants:
 *
 * <ul>
 *   <li>Each graph instances "owns" the nodes is creates. The behaviour of operations on nodes a
 *       graph does not own is undefined.
 *   <li>{@code Digraph} assumes immutability of node labels, much like {@link HashMap} assumes it
 *       for keys.
 *   <li>Mutating the underlying graph invalidates any sets and iterators backed by it.
 *   <li>Nodes can be added and removed concurrently. Edges can be added and removed concurrently
 *       too. While it is thread safe to add or remove edge, these operations are not atomic. Graph
 *       can be observable in inconsistent state during this operations, for instance: edge linked
 *       to only one node.
 *   <li>
 * </ul>
 *
 * <p>Each node stores successor and predecessor adjacency sets using a representation that
 * dynamically changes with size: small sets are stored as arrays, large sets using hash tables.
 * This representation provides significant space and time performance improvements upon two prior
 * versions: the earliest used only HashSets; a later version used linked lists, as described in
 * Cormen, Leiserson &amp; Rivest.
 */
public final class Digraph<T> implements Cloneable {

  /** Maps labels to nodes, which are in strict 1:1 correspondence. */
  private final Map<T, Node<T>> nodes = new ConcurrentHashMap<>();

  /**
   * Construct an empty Digraph.
   */
  public Digraph() {}

  /**
   * Sanity-check: assert that a node is indeed a member of this graph and not
   * another one.  Perform this check whenever a function is supplied a node by
   * the user.
   */
  private final void checkNode(Node<T> node) {
    if (getNode(node.getLabel()) != node) {
      throw new IllegalArgumentException("node " + node
                                         + " is not a member of this graph");
    }
  }

  /**
   * Adds a directed edge between the nodes labelled 'from' and 'to', creating
   * them if necessary.
   *
   * @return true iff the edge was not already present.
   */
  public boolean addEdge(T from, T to) {
    Node<T> fromNode = createNode(from);
    Node<T> toNode   = createNode(to);
    return addEdge(fromNode, toNode);
  }

  /**
   * Adds a directed edge between the specified nodes, which must exist and
   * belong to this graph.
   *
   * @return true iff the edge was not already present.
   *
   * Note: multi-edges are ignored.  Self-edges are permitted.
   */
  public boolean addEdge(Node<T> fromNode, Node<T> toNode) {
    checkNode(fromNode);
    checkNode(toNode);
    return fromNode.addEdge(toNode);
  }

  /**
   * Returns true iff the graph contains an edge between the
   * specified nodes, which must exist and belong to this graph.
   */
  public boolean containsEdge(Node<T> fromNode, Node<T> toNode) {
    checkNode(fromNode);
    checkNode(toNode);
    // TODO(bazel-team): (2009) iterate only over the shorter of from.succs, to.preds.
    return fromNode.getSuccessors().contains(toNode);
  }

  /**
   * Removes the edge between the specified nodes.  Idempotent: attempts to
   * remove non-existent edges have no effect.
   *
   * @return true iff graph changed.
   */
  public boolean removeEdge(Node<T> fromNode, Node<T> toNode) {
    checkNode(fromNode);
    checkNode(toNode);
    return fromNode.removeEdge(toNode);
  }

  /**
   * Remove all nodes and edges.
   */
  public void clear() {
    nodes.clear();
  }

  @Override
  public String toString() {
    return "Digraph[" + getNodeCount() + " nodes]";
  }

  @Override
  public int hashCode() {
    throw new UnsupportedOperationException(); // avoid nondeterminism
  }

  /**
   * Returns true iff the two graphs are equivalent, i.e. have the same set
   * of node labels, with the same connectivity relation.
   *
   * O(n^2) in the worst case, i.e. equivalence.  The algorithm could be speed up by
   * close to a factor 2 in the worst case by a more direct implementation instead
   * of using isSubgraph twice.
   */
  @Override
  public boolean equals(Object thatObject) {
    /* If this graph is a subgraph of thatObject, then we know that thatObject is of
     * type Digraph<?> and thatObject can be cast to this type.
     */
    return isSubgraph(thatObject) && ((Digraph<?>) thatObject).isSubgraph(this);
  }

  /**
   * Returns true iff this graph is a subgraph of the argument. This means that this graph's nodes
   * are a subset of those of the argument; moreover, for each node of this graph the set of
   * successors is a subset of those of the corresponding node in the argument graph.
   *
   * This algorithm is O(n^2), but linear in the total sizes of the graphs.
   */
  public boolean isSubgraph(Object thatObject) {
    if (this == thatObject) {
      return true;
    }
    if (!(thatObject instanceof Digraph)) {
      return false;
    }

    @SuppressWarnings("unchecked")
    Digraph<T> that = (Digraph<T>) thatObject;
    if (this.getNodeCount() > that.getNodeCount()) {
      return false;
    }
    for (Node<T> n1: nodes.values()) {
      Node<T> n2 = that.getNodeMaybe(n1.getLabel());
      if (n2 == null) {
        return false; // 'that' is missing a node
      }

      // Now compare the successor relations.
      // Careful:
      // - We can't do simple equality on the succs-sets because the
      //   nodes belong to two different graphs!
      // - There's no need to check both predecessor and successor
      //   relations, either one is sufficient.
      Collection<Node<T>> n1succs = n1.getSuccessors();
      Collection<Node<T>> n2succs = n2.getSuccessors();
      if (n1succs.size() > n2succs.size()) {
        return false;
      }
      // foreach successor of n1, ensure n2 has a similarly-labeled succ.
      for (Node<T> succ1: n1succs) {
        Node<T> succ2 = that.getNodeMaybe(succ1.getLabel());
        if (succ2 == null) {
          return false;
        }
        if (!n2succs.contains(succ2)) {
          return false;
        }
      }
    }
    return true;
  }

  /**
   * Returns a duplicate graph with the same set of node labels and the same
   * connectivity relation.  The labels themselves are not cloned.
   */
  @Override
  public Digraph<T> clone() {
    final Digraph<T> that = new Digraph<T>();
    visitNodesBeforeEdges(
        new AbstractGraphVisitor<T>() {
          @Override
          public void visitEdge(Node<T> lhs, Node<T> rhs) {
            that.addEdge(lhs.getLabel(), rhs.getLabel());
          }

          @Override
          public void visitNode(Node<T> node) {
            that.createNode(node.getLabel());
          }
        },
        nodes.values(),
        null);
    return that;
  }

  /** Returns a deterministic immutable copy of the nodes of this graph. */
  public Collection<Node<T>> getNodes(final Comparator<? super T> comparator) {
    return ImmutableList.sortedCopyOf(comparing(Node::getLabel, comparator), nodes.values());
  }

  /**
   * Returns an immutable view of the nodes of this graph.
   *
   * Note: we have to return Collection and not Set because values() returns
   * one: the 'nodes' HashMap doesn't know that it is injective.  :-(
   */
  public Collection<Node<T>> getNodes() {
    return Collections.unmodifiableCollection(nodes.values());
  }

  /**
   * @return the set of root nodes: those with no predecessors.
   *
   * NOTE: in a cyclic graph, there may be nodes that are not reachable from
   * any "root".
   */
  public Set<Node<T>> getRoots() {
    Set<Node<T>> roots = new HashSet<>();
    for (Node<T> node: nodes.values()) {
      if (!node.hasPredecessors()) {
        roots.add(node);
      }
    }
    return roots;
  }

  /**
   * @return the set of leaf nodes: those with no successors.
   */
  public Set<Node<T>> getLeaves() {
    Set<Node<T>> leaves = new HashSet<>();
    for (Node<T> node: nodes.values()) {
      if (!node.hasSuccessors()) {
        leaves.add(node);
      }
    }
    return leaves;
  }

  /**
   * @return an immutable view of the set of labels of this graph's nodes.
   */
  public Set<T> getLabels() {
    return Collections.unmodifiableSet(nodes.keySet());
  }

  /**
   * Finds and returns the node with the specified label.  If there is no such
   * node, an exception is thrown.  The null pointer is not a valid label.
   *
   * @return the node whose label is "label".
   * @throws IllegalArgumentException if no node was found with the specified
   * label.
   */
  public Node<T> getNode(T label) {
    if (label == null) {
      throw new NullPointerException();
    }
    Node<T> node = nodes.get(label);
    if (node == null) {
      throw new IllegalArgumentException("No such node label: " + label);
    }
    return node;
  }

  /**
   * Find the node with the specified label.  Returns null if it doesn't exist.
   * The null pointer is not a valid label.
   *
   * @return the node whose label is "label", or null if it was not found.
   */
  public Node<T> getNodeMaybe(T label) {
    if (label == null) {
      throw new NullPointerException();
    }
    return nodes.get(label);
  }

  /**
   * @return the number of nodes in the graph.
   */
  public int getNodeCount() {
    return nodes.size();
  }

  /**
   * @return the number of edges in the graph.
   *
   * Note: expensive! Useful when asserting against mutations though.
   */
  public int getEdgeCount() {
    int edges = 0;
    for (Node<T> node: nodes.values()) {
      edges += node.getSuccessors().size();
    }
    return edges;
  }

  /**
   * Find or create a node with the specified label. This is the <i>only</i> factory of Nodes. The
   * null pointer is not a valid label.
   */
  public Node<T> createNode(T label) {
    return nodes.computeIfAbsent(label, Digraph::createNodeNative);
  }

  private static <T> Node<T> createNodeNative(T label) {
    Preconditions.checkNotNull(label);
    return new Node<>(label);
  }

  /******************************************************************
   *                                                                *
   *                        Graph Algorithms                        *
   *                                                                *
   ******************************************************************/

  /**
   * These only manipulate the graph through methods defined above.
   */

  /**
   * Returns true iff the graph is cyclic.  Time: O(n).
   */
  public boolean isCyclic() {

    // To detect cycles, we use a colored depth-first search. All nodes are
    // initially marked white.  When a node is encountered, it is marked grey,
    // and when its descendants are completely visited, it is marked black.
    // If a grey node is ever encountered, then there is a cycle.
    final Object WHITE = null; // i.e. not present in nodeToColor, the default.
    final Object GREY  = new Object();
    final Object BLACK = new Object();
    final Map<Node<T>, Object> nodeToColor = new HashMap<>(); // empty => all white

    class CycleDetector { /* defining a class gives us lexical scope */
      boolean visit(Node<T> node) {
        nodeToColor.put(node, GREY);
        for (Node<T> succ: node.getSuccessors()) {
          if (nodeToColor.get(succ) == GREY) {
            return true;
          } else if (nodeToColor.get(succ) == WHITE) {
            if (visit(succ)) {
              return true;
            }
          }
        }
        nodeToColor.put(node, BLACK);
        return false;
      }
    }

    CycleDetector detector = new CycleDetector();
    for (Node<T> node: nodes.values()) {
      if (nodeToColor.get(node) == WHITE) {
        if (detector.visit(node)) {
          return true;
        }
      }
    }
    return false;
  }

  /**
   * Returns the strong component graph of "this".  That is, returns a new
   * acyclic graph in which all strongly-connected components in the original
   * graph have been "fused" into a single node.
   *
   * @return a new graph, whose node labels are sets of nodes of the
   * original graph.  (Do not get confused as to which graph each
   * set of Nodes belongs!)
   */
  public Digraph<Set<Node<T>>> getStrongComponentGraph() {
    Collection<Set<Node<T>>> sccs = getStronglyConnectedComponents();
    Digraph<Set<Node<T>>> scGraph = createImageUnderPartition(sccs);
    scGraph.removeSelfEdges(); // scGraph should be acyclic: no self-edges
    return scGraph;
  }

  /**
   * Returns a partition of the nodes of this graph into sets, each set being
   * one strongly-connected component of the graph.
   */
  public Collection<Set<Node<T>>> getStronglyConnectedComponents() {
    final List<Set<Node<T>>> sccs = new ArrayList<>();
    NodeSetReceiver<T> r = sccs::add;
    SccVisitor<T> v = new SccVisitor<>();
    for (Node<T> node : nodes.values()) {
      v.visit(r, node);
    }
    return sccs;
  }

  /**
   * <p> Given a partition of the graph into sets of nodes, returns the image
   * of this graph under the function which maps each node to the
   * partition-set in which it appears.  The labels of the new graph are the
   * (immutable) sets of the partition, and the edges of the new graph are the
   * edges of the original graph, mapped via the same function. </p>
   *
   * <p> Note: the resulting graph may contain self-edges.  If these are not
   * wanted, call <code>removeSelfEdges()</code>> on the result. </p>
   *
   * <p> Interesting special case: if the partition is the set of
   * strongly-connected components, the result of this function is the
   * strong-component graph. </p>
   */
  public Digraph<Set<Node<T>>>
    createImageUnderPartition(Collection<Set<Node<T>>> partition) {

    // Build mapping function: each node label is mapped to its equiv class:
    Map<T, Set<Node<T>>> labelToImage = new HashMap<>();
    for (Set<Node<T>> set: partition) {
      // It's important to use immutable sets of node labels when sets are keys
      // in a map; see ImmutableSet class for explanation.
      Set<Node<T>> imageSet = ImmutableSet.copyOf(set);
      for (Node<T> node: imageSet) {
        labelToImage.put(node.getLabel(), imageSet);
      }
    }

    if (labelToImage.size() != getNodeCount()) {
      throw new IllegalArgumentException(
          "createImageUnderPartition(): argument is not a partition");
    }

    return createImageUnderMapping(labelToImage);
  }

  /**
   * Returns the image of this graph in a given function, expressed as a
   * mapping from labels to some other domain.
   */
  public <IMAGE> Digraph<IMAGE>
    createImageUnderMapping(Map<T, IMAGE> map) {
    Digraph<IMAGE> imageGraph = new Digraph<>();

    for (Node<T> fromNode: nodes.values()) {
      T fromLabel = fromNode.getLabel();

      IMAGE fromImage = map.get(fromLabel);
      if (fromImage == null) {
        throw new IllegalArgumentException(
            "Incomplete function: undefined for " + fromLabel);
      }
      imageGraph.createNode(fromImage);

      for (Node<T> toNode: fromNode.getSuccessors()) {
        T toLabel = toNode.getLabel();

        IMAGE toImage = map.get(toLabel);
        if (toImage == null) {
          throw new IllegalArgumentException(
            "Incomplete function: undefined for " + toLabel);
        }
        imageGraph.addEdge(fromImage, toImage);
      }
    }

    return imageGraph;
  }

  /**
   * Removes any self-edges (x,x) in this graph.
   */
  public void removeSelfEdges() {
    for (Node<T> node: nodes.values()) {
      removeEdge(node, node);
    }
  }

  /**
   * Finds the shortest directed path from "fromNode" to "toNode".  The path is
   * returned as an ordered list of nodes, including both endpoints.  Returns
   * null if there is no path.  Uses breadth-first search.  Running time is
   * O(n).
   */
  public List<Node<T>> getShortestPath(Node<T> fromNode,
                                           Node<T> toNode) {
    checkNode(fromNode);
    checkNode(toNode);

    if (fromNode == toNode) {
      return Collections.singletonList(fromNode);
    }

    Map<Node<T>, Node<T>> pathPredecessor = new HashMap<>();

    Set<Node<T>> marked = new HashSet<>();

    LinkedList<Node<T>> queue = new LinkedList<>();
    queue.addLast(fromNode);
    marked.add(fromNode);

    while (!queue.isEmpty()) {
      Node<T> u = queue.removeFirst();
      for (Node<T> v: u.getSuccessors()) {
        if (marked.add(v)) {
          pathPredecessor.put(v, u);
          if (v == toNode) {
            return getPathToTreeNode(pathPredecessor, v); // found a path
          }
          queue.addLast(v);
        }
      }
    }
    return null; // no path
  }

  /**
   * Given a tree (expressed as a map from each node to its parent), and a
   * starting node, returns the path from the root of the tree to 'node' as a
   * list.
   */
  public static <X> List<X> getPathToTreeNode(Map<X, X> tree, X node) {
    List<X> path = new ArrayList<>();
    while (node != null) {
      path.add(node);
      node = tree.get(node); // get parent
    }
    Collections.reverse(path);
    return path;
  }

  /**
   * Returns the nodes of an acyclic graph in topological order
   * [a.k.a "reverse post-order" of depth-first search.]
   *
   * A topological order is one such that, if (u, v) is a path in
   * acyclic graph G, then u is before v in the topological order.
   * In other words "tails before heads" or "roots before leaves".
   *
   * @return The nodes of the graph, in a topological order
   */
  public List<Node<T>> getTopologicalOrder() {
    List<Node<T>> order = getPostorder();
    Collections.reverse(order);
    return order;
  }

  /**
   * Returns the nodes of an acyclic graph in topological order
   * [a.k.a "reverse post-order" of depth-first search.]
   *
   * A topological order is one such that, if (u, v) is a path in
   * acyclic graph G, then u is before v in the topological order.
   * In other words "tails before heads" or "roots before leaves".
   *
   * If an ordering is given, returns a specific topological order from the set
   * of all topological orders; if no ordering given, returns an arbitrary
   * (nondeterministic) one, but is a bit faster because no sorting needs to be
   * done for each node.
   *
   * @param edgeOrder the ordering in which edges originating from the same node
   *     are visited.
   * @return The nodes of the graph, in a topological order
   */
  public List<Node<T>> getTopologicalOrder(Comparator<? super T> edgeOrder) {
    CollectingVisitor<T> visitor = new CollectingVisitor<>();
    DFS<T> visitation = new DFS<>(DFS.Order.POSTORDER, edgeOrder, false);
    visitor.beginVisit();
    for (Node<T> node : getNodes(edgeOrder)) {
      visitation.visit(node, visitor);
    }
    visitor.endVisit();

    List<Node<T>> order = visitor.getVisitedNodes();
    Collections.reverse(order);
    return order;
  }

  /**
   * Returns the nodes of an acyclic graph in post-order.
   */
  public List<Node<T>> getPostorder() {
    CollectingVisitor<T> collectingVisitor = new CollectingVisitor<>();
    visitPostorder(collectingVisitor);
    return collectingVisitor.getVisitedNodes();
  }

  /**
   * Returns the (immutable) set of nodes reachable from node 'n' (reflexive
   * transitive closure).
   */
  public Set<Node<T>> getFwdReachable(Node<T> n) {
    return getFwdReachable(Collections.singleton(n));
  }

  /**
   * Returns the (immutable) set of nodes reachable from any node in {@code
   * startNodes} (reflexive transitive closure).
   */
  public Set<Node<T>> getFwdReachable(Collection<Node<T>> startNodes) {
    // This method is intentionally not static, to permit future expansion.
    DFS<T> dfs = new DFS<T>(DFS.Order.PREORDER, false);
    for (Node<T> n : startNodes) {
      dfs.visit(n, new AbstractGraphVisitor<>());
    }
    return dfs.getMarked();
  }

  /**
   * Returns the (immutable) set of nodes that reach node 'n' (reflexive
   * transitive closure).
   */
  public Set<Node<T>> getBackReachable(Node<T> n) {
    return getBackReachable(Collections.singleton(n));
  }

  /**
   * Returns the (immutable) set of nodes that reach some node in {@code
   * startNodes} (reflexive transitive closure).
   */
  public Set<Node<T>> getBackReachable(Collection<Node<T>> startNodes) {
    // This method is intentionally not static, to permit future expansion.
    DFS<T> dfs = new DFS<T>(DFS.Order.PREORDER, true);
    for (Node<T> n : startNodes) {
      dfs.visit(n, new AbstractGraphVisitor<>());
    }
    return dfs.getMarked();
  }

  /**
   * Removes the specified node in the graph.
   *
   * <p>If preserveOrder flag is set than after removing node this method connects all predecessors
   * and successors.
   *
   * <p>Let's consider graph
   *
   * <pre>
   * a -> n -> c
   * b -> n -> d
   * </pre>
   *
   * After n removed the following edges will be added
   *
   * <pre>
   * a -> c
   * a -> d
   * b -> c
   * b -> d
   * </pre>
   *
   * @param node the node to remove (must be in the graph).
   * @param preserveOrder see removeNode(T, boolean).
   */
  public Collection<Node<T>> removeNode(Node<T> node, boolean preserveOrder) {
    checkNode(node);

    Collection<Node<T>> predecessors = node.removeAllPredecessors();
    Collection<Node<T>> successors = node.removeAllSuccessors();

    List<Node<T>> neighbours = Collections.emptyList();

    if (preserveOrder) {
      neighbours = new ArrayList<>(successors.size() + predecessors.size());
      neighbours.addAll(successors);
      neighbours.addAll(predecessors);

      for (Node<T> p : predecessors) {
        for (Node<T> s : successors) {
          p.addEdge(s);
        }
      }
    }

    Object del = nodes.remove(node.getLabel());
    if (del != node) {
      throw new IllegalStateException(del + " " + node);
    }

    return neighbours;
  }

  /**
   * Extracts the subgraph G' of this graph G, containing exactly the nodes
   * specified by the labels in V', and preserving the original
   * <i>transitive</i> graph relation among those nodes. </p>
   *
   * @param subset a subset of the labels of this graph; the resulting graph
   * will have only the nodes with these labels.
   */
  public Digraph<T> extractSubgraph(final Set<T> subset) {
    Digraph<T> subgraph = this.clone();
    subgraph.subgraph(subset);
    return subgraph;
  }

  /**
   * Removes all nodes from this graph except those whose label is an element of {@code keepLabels}.
   * Edges are added so as to preserve the <i>transitive</i> closure relation.
   *
   * @param keepLabels a subset of the labels of this graph; the resulting graph will have only the
   *     nodes with these labels.
   */
  private void subgraph(final Set<T> keepLabels) {
    // This algorithm does the following:
    // Let keep = nodes that have labels in keepLabels.
    // Let toRemove = nodes \ keep. reachables = successors and predecessors of keep in nodes.
    // reachables is the subset of nodes of remove that are an immediate neighbor of some node in
    // keep.
    //
    // Removes all nodes of reachables from keepLabels.
    // Until reachables is empty:
    //   Takes n from reachables
    //   for all s in succ(n)
    //     for all p in pred(n)
    //       add the edge (p, s)
    //     add s to reachables
    //   for all p in pred(n)
    //     add p to reachables
    //   Remove n and its edges
    //
    // A few adjustments are needed to do the whole computation.

    final Set<Node<T>> toRemove = new HashSet<>();
    final Set<Node<T>> keepNeighbors = new HashSet<>();

    // Look for all nodes if they are to be kept or removed
    for (Node<T> node : nodes.values()) {
      if (keepLabels.contains(node.getLabel())) {
        // Node is to be kept
        keepNeighbors.addAll(node.getPredecessors());
        keepNeighbors.addAll(node.getSuccessors());
      } else {
        // node is to be removed.
        toRemove.add(node);
      }
    }

    if (toRemove.isEmpty()) {
      // This premature return is needed to avoid 0-size priority queue creation.
      return;
    }

    // We use a priority queue to look for low-order nodes first so we don't propagate the high
    // number of paths of high-order nodes making the time consumption explode.
    // For perfect results we should reorder the set each time we add a new edge but this would
    // be too expensive, so this is a good enough approximation.
    final PriorityQueue<Node<T>> reachables =
        new PriorityQueue<>(
            toRemove.size(),
            comparingLong(arg -> (long) arg.numPredecessors() * (long) arg.numSuccessors()));

    // Construct the reachables queue with the list of successors and predecessors of keep in
    // toRemove.
    keepNeighbors.retainAll(toRemove);
    reachables.addAll(keepNeighbors);
    toRemove.removeAll(reachables);

    // Remove nodes, least connected first, preserving reachability.
    while (!reachables.isEmpty()) {

      Node<T> node = reachables.poll();

      Collection<Node<T>> neighbours = removeNode(node, /*preserveOrder*/ true);

      for (Node<T> neighbour : neighbours) {
        if (toRemove.remove(neighbour)) {
          reachables.add(neighbour);
        }
      }
    }

    // Final cleanup for non-reachable nodes.
    for (Node<T> node : toRemove) {
      removeNode(node, false);
    }
  }

  @FunctionalInterface
  private interface NodeSetReceiver<T> {
    void accept(Set<Node<T>> nodes);
  }

  /**
   * Find strongly connected components using path-based strong component
   * algorithm. This has the advantage over the default method of returning
   * the components in postorder.
   *
   * We visit nodes depth-first, keeping track of the order that
   * we visit them in (preorder). Our goal is to find the smallest node (in
   * this preorder of visitation) reachable from a given node. We keep track of the
   * smallest node pointed to so far at the top of a stack. If we ever find an
   * already-visited node, then if it is not already part of a component, we
   * pop nodes from that stack until we reach this already-visited node's number
   * or an even smaller one.
   *
   * Once the depth-first visitation of a node is complete, if this node's
   * number is at the top of the stack, then it is the "first" element visited
   * in its strongly connected component. Hence we pop all elements that were
   * pushed onto the visitation stack and put them in a strongly connected
   * component with this one, then send a passed-in {@link Digraph.NodeSetReceiver} this component.
   */
  private class SccVisitor<T> {
    // Nodes already assigned to a strongly connected component.
    private final Set<Node<T>> assigned = new HashSet<>();

    // The order each node was visited in.
    private final Map<Node<T>, Integer> preorder = new HashMap<>();

    // Stack of all nodes visited whose SCC has not yet been determined. When an SCC is found,
    // that SCC is an initial segment of this stack, and is popped off. Every time a new node is
    // visited, it is put on this stack.
    private final List<Node<T>> stack = new ArrayList<>();

    // Stack of visited indices for the first-visited nodes in each of their known-so-far
    // strongly connected components. A node pushes its index on when it is visited. If any of
    // its successors have already been visited and are not in an already-found strongly connected
    // component, then, since the successor was already visited, it and this node must be part of a
    // cycle. So every node visited since the successor is actually in the same strongly connected
    // component. In this case, preorderStack is popped until the top is at most the successor's
    // index.
    //
    // After all descendants of a node have been visited, if the top element of preorderStack is
    // still the current node's index, then it was the first element visited of the current strongly
    // connected component. So all nodes on {@code stack} down to the current node are in its
    // strongly connected component. And the node's index is popped from preorderStack.
    private final List<Integer> preorderStack = new ArrayList<>();

    // Index of node being visited.
    private int counter = 0;

    private void visit(NodeSetReceiver<T> visitor, Node<T> node) {
      if (preorder.containsKey(node)) {
        // This can only happen if this was a non-recursive call, and a previous
        // visit call had already visited node.
        return;
      }
      preorder.put(node, counter);
      stack.add(node);
      preorderStack.add(counter++);
      int preorderLength = preorderStack.size();
      for (Node<T> succ : node.getSuccessors()) {
        Integer succPreorder = preorder.get(succ);
        if (succPreorder == null) {
          visit(visitor, succ);
        } else {
          // Does succ not already belong to an SCC? If it doesn't, then it
          // must be in the same SCC as node. The "starting node" of this SCC
          // must have been visited before succ (or is succ itself).
          if (!assigned.contains(succ)) {
            while (preorderStack.get(preorderStack.size() - 1) > succPreorder) {
              preorderStack.remove(preorderStack.size() - 1);
            }
          }
        }
      }
      if (preorderLength == preorderStack.size()) {
        // If the length of the preorderStack is unchanged, we did not find any earlier-visited
        // nodes that were part of a cycle with this node. So this node is the first-visited
        // element in its strongly connected component, and we collect the component.
        preorderStack.remove(preorderStack.size() - 1);
        Set<Node<T>> scc = new HashSet<>();
        Node<T> compNode;
        do {
          compNode = stack.remove(stack.size() - 1);
          assigned.add(compNode);
          scc.add(compNode);
        } while (!node.equals(compNode));
        visitor.accept(scc);
      }
    }
  }

  /********************************************************************
   *                                                                  *
   *                    Orders, traversals and visitors               *
   *                                                                  *
   ********************************************************************/

  /**
   * A visitation over all the nodes in the graph that invokes
   * <code>visitor.visitNode()</code> for each node in a depth-first
   * post-order: each node is visited <i>after</i> each of its successors; the
   * order in which edges are traversed is the order in which they were added
   * to the graph.  <code>visitor.visitEdge()</code> is not called.
   *
   * @param startNodes the set of nodes from which to begin the visitation.
   */
  public void visitPostorder(GraphVisitor<T> visitor,
                             Iterable<Node<T>> startNodes) {
    visitDepthFirst(visitor, DFS.Order.POSTORDER, false, startNodes);
  }

  /**
   * Equivalent to {@code visitPostorder(visitor, getNodes())}.
   */
  public void visitPostorder(GraphVisitor<T> visitor) {
    visitPostorder(visitor, nodes.values());
  }

  /**
   * A visitation over all the nodes in the graph that invokes
   * <code>visitor.visitNode()</code> for each node in a depth-first
   * pre-order: each node is visited <i>before</i> each of its successors; the
   * order in which edges are traversed is the order in which they were added
   * to the graph.  <code>visitor.visitEdge()</code> is not called.
   *
   * @param startNodes the set of nodes from which to begin the visitation.
   */
  public void visitPreorder(GraphVisitor<T> visitor,
                            Iterable<Node<T>> startNodes) {
    visitDepthFirst(visitor, DFS.Order.PREORDER, false, startNodes);
  }

  /**
   * Equivalent to {@code visitPreorder(visitor, getNodes())}.
   */
  public void visitPreorder(GraphVisitor<T> visitor) {
    visitPreorder(visitor, nodes.values());
  }

  /**
   * A visitation over all the nodes in the graph in depth-first order.  See
   * DFS constructor for meaning of 'order' and 'transpose' parameters.
   *
   * @param startNodes the set of nodes from which to begin the visitation.
   */
  public void visitDepthFirst(GraphVisitor<T> visitor,
                              DFS.Order order,
                              boolean transpose,
                              Iterable<Node<T>> startNodes) {
    DFS<T> visitation = new DFS<>(order, transpose);
    visitor.beginVisit();
    for (Node<T> node: startNodes) {
      visitation.visit(node, visitor);
    }
    visitor.endVisit();
  }

  private static <T> Comparator<Node<T>> makeNodeComparator(
      final Comparator<? super T> comparator) {
    return comparing(Node::getLabel, comparator::compare);
  }

  /**
   * Given {@code unordered}, a collection of nodes and a (possibly null) {@code comparator} for
   * their labels, returns a sorted collection if {@code comparator} is non-null, otherwise returns
   * {@code unordered}.
   */
  private static <T> Collection<Node<T>> maybeOrderCollection(
      Collection<Node<T>> unordered, @Nullable final Comparator<? super T> comparator) {
    return comparator == null
        ? unordered
        : ImmutableList.sortedCopyOf(makeNodeComparator(comparator), unordered);
  }

  private void visitNodesBeforeEdges(
      GraphVisitor<T> visitor,
      Iterable<Node<T>> startNodes,
      @Nullable Comparator<? super T> comparator) {
    visitor.beginVisit();
    for (Node<T> fromNode: startNodes) {
      visitor.visitNode(fromNode);
      for (Node<T> toNode : maybeOrderCollection(fromNode.getSuccessors(), comparator)) {
        visitor.visitEdge(fromNode, toNode);
      }
    }
    visitor.endVisit();
  }

  /**
   * A visitation over the graph that visits all nodes and edges in topological order
   * such that each node is visited before any edge coming out of that node; ties among nodes are
   * broken using the provided {@code comparator} if not null; edges are visited in order specified
   * by the comparator, <b>not</b> topological order of the target nodes.
   */
  public void visitNodesBeforeEdges(
      GraphVisitor<T> visitor, @Nullable Comparator<? super T> comparator) {
    visitNodesBeforeEdges(
        visitor,
        comparator == null ? getTopologicalOrder() : getTopologicalOrder(comparator),
        comparator);
  }
}