* src/tgbaalgos/randomgraph.cc, src/tgbaalgos/randomgraph.hh: Add option to generate a complete deterministic automaton. * src/tgbatest/randtgba.cc: Test it.
234 lines
6.2 KiB
C++
234 lines
6.2 KiB
C++
// -*- coding: utf-8 -*-
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// Copyright (C) 2008, 2009, 2010, 2012, 2013, 2014 Laboratoire de
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// Recherche et Développement de l'Epita (LRDE).
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// Copyright (C) 2004, 2005, 2007 Laboratoire d'Informatique de
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// Paris 6 (LIP6), département Systèmes Répartis Coopératifs (SRC),
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// Université Pierre et Marie Curie.
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//
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// This file is part of Spot, a model checking library.
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//
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// Spot is free software; you can redistribute it and/or modify it
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// under the terms of the GNU General Public License as published by
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// the Free Software Foundation; either version 3 of the License, or
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// (at your option) any later version.
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//
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// Spot is distributed in the hope that it will be useful, but WITHOUT
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// ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
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// or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
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// License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with this program. If not, see <http://www.gnu.org/licenses/>.
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#include "randomgraph.hh"
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#include "tgba/tgbagraph.hh"
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#include "misc/random.hh"
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#include "misc/bddlt.hh"
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#include "ltlast/atomic_prop.hh"
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#include <sstream>
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#include <list>
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#include <set>
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#include <iterator>
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#include <vector>
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namespace spot
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{
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namespace
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{
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unsigned
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random_deterministic_labels_rec(std::vector<bdd>& labels, int *props,
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int props_n, bdd current, unsigned n)
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{
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if (n > 1 && props_n >= 1)
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{
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bdd ap = bdd_ithvar(*props);
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++props;
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--props_n;
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// There are m labels generated from "current & ap"
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// and n - m labels generated from "current & !ap"
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unsigned m = rrand(1, n - 1);
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if (2 * m < n)
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{
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m = n - m;
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ap = !ap;
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}
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unsigned res = random_deterministic_labels_rec(labels, props,
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props_n,
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current & ap, m);
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res += random_deterministic_labels_rec(labels, props, props_n,
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current & !ap, n - res);
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return res;
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}
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else
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{
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labels.push_back(current);
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return 1;
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}
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}
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std::vector<bdd>
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random_deterministic_labels(int *props, int props_n, unsigned n)
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{
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std::vector<bdd> bddvec;
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random_deterministic_labels_rec(bddvec, props, props_n, bddtrue, n);
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return bddvec;
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}
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acc_cond::mark_t
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random_acc_cond(tgba_digraph_ptr aut, unsigned n_accs, float a)
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{
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acc_cond::mark_t m = 0U;
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for (unsigned i = 0U; i < n_accs; ++i)
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if (drand() < a)
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m |= aut->acc().mark(i);
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return m;
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}
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bdd
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random_labels(int* props, int props_n, float t)
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{
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int val = 0;
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int size = 0;
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bdd p = bddtrue;
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while (props_n)
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{
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if (size == 8 * sizeof(int))
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{
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p &= bdd_ibuildcube(val, size, props);
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props += size;
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val = 0;
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size = 0;
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}
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val <<= 1;
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val |= (drand() < t);
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++size;
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--props_n;
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}
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if (size > 0)
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p &= bdd_ibuildcube(val, size, props);
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return p;
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}
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}
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tgba_digraph_ptr
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random_graph(int n, float d,
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const ltl::atomic_prop_set* ap, const bdd_dict_ptr& dict,
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unsigned n_accs, float a, float t, bool deterministic)
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{
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assert(n > 0);
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auto res = make_tgba_digraph(dict);
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int props_n = ap->size();
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int* props = new int[props_n];
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int pi = 0;
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for (auto i: *ap)
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props[pi++] = dict->register_proposition(i, res);
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res->set_acceptance_conditions(n_accs);
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// Using std::unordered_set instead of std::set for these sets is 3
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// times slower (tested on a 50000 nodes example).
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typedef std::set<int> node_set;
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node_set nodes_to_process;
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node_set unreachable_nodes;
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res->new_states(n);
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std::vector<unsigned> state_randomizer(n);
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state_randomizer[0] = 0;
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nodes_to_process.insert(0);
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for (int i = 1; i < n; ++i)
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{
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state_randomizer[i] = i;
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unreachable_nodes.insert(i);
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}
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// We want to connect each node to a number of successors between
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// 1 and n. If the probability to connect to each successor is d,
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// the number of connected successors follows a binomial distribution.
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barand bin(n - 1, d);
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while (!nodes_to_process.empty())
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{
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auto src = *nodes_to_process.begin();
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nodes_to_process.erase(nodes_to_process.begin());
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// Choose a random number of successors (at least one), using
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// a binomial distribution.
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unsigned nsucc = 1 + bin.rand();
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bool saw_unreachable = false;
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// Create NSUCC random labels.
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std::vector<bdd> labels;
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if (deterministic)
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{
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labels = random_deterministic_labels(props, props_n, nsucc);
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// if nsucc > 2^props_n, we cannot produce nsucc deterministic
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// transitions so we set it to labels.size()
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nsucc = labels.size();
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}
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else
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for (unsigned i = 0; i < nsucc; ++i)
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labels.push_back(random_labels(props, props_n, t));
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int possibilities = n;
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unsigned dst;
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for (auto& l: labels)
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{
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acc_cond::mark_t m = random_acc_cond(res, n_accs, a);
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// No connection to unreachable successors so far. This
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// is our last chance, so force it now.
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if (--nsucc == 0
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&& !unreachable_nodes.empty()
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&& !saw_unreachable)
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{
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// Pick a random unreachable node.
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int index = mrand(unreachable_nodes.size());
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node_set::const_iterator i = unreachable_nodes.begin();
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std::advance(i, index);
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// Link it from src.
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res->new_transition(src, *i, l, m);
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nodes_to_process.insert(*i);
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unreachable_nodes.erase(*i);
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break;
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}
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// Pick the index of a random node.
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int index = mrand(possibilities--);
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// Permute it with state_randomizer[possibilities], so
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// we cannot pick it again.
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dst = state_randomizer[index];
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state_randomizer[index] = state_randomizer[possibilities];
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state_randomizer[possibilities] = dst;
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res->new_transition(src, dst, l, m);
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auto j = unreachable_nodes.find(dst);
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if (j != unreachable_nodes.end())
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{
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nodes_to_process.insert(dst);
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unreachable_nodes.erase(j);
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saw_unreachable = true;
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}
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}
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// The node must have at least one successor.
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assert(res->get_graph().state_storage(src).succ);
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}
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// All nodes must be reachable.
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assert(unreachable_nodes.empty());
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delete[] props;
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return res;
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}
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}
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