alarsyo/spot
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity

rename src/tgbaalgos/ as src/twaalgos/

Browse source 
Automatic mass renaming.

* src/tgbaalgos/: Rename as...
* src/twaalgos/: ... this.
* README, configure.ac, iface/ltsmin/modelcheck.cc, src/Makefile.am,
src/bin/autfilt.cc, src/bin/common_aoutput.cc,
src/bin/common_aoutput.hh, src/bin/common_output.hh,
src/bin/common_post.hh, src/bin/dstar2tgba.cc, src/bin/ltl2tgba.cc,
src/bin/ltl2tgta.cc, src/bin/ltlcross.cc, src/bin/ltldo.cc,
src/bin/ltlfilt.cc, src/bin/randaut.cc, src/dstarparse/dra2ba.cc,
src/dstarparse/nra2nba.cc, src/dstarparse/nsa2tgba.cc,
src/graphtest/twagraph.cc, src/kripke/kripkeprint.cc,
src/ltlvisit/contain.cc, src/ltlvisit/contain.hh,
src/ltlvisit/exclusive.cc, src/taalgos/emptinessta.hh,
src/tgbatest/checkpsl.cc, src/tgbatest/checkta.cc,
src/tgbatest/complementation.cc, src/tgbatest/emptchk.cc,
src/tgbatest/ltl2tgba.cc, src/tgbatest/ltlprod.cc,
src/tgbatest/randtgba.cc, src/tgbatest/taatgba.cc, src/twa/twa.cc,
src/twa/twagraph.hh, src/twa/twasafracomplement.cc,
wrap/python/spot_impl.i: Adjust.
This commit is contained in:
Alexandre Duret-Lutz 2015-04-22 17:52:27 +02:00
parent 703fbd0e99
commit de529df59f
159 changed files with 260 additions and 272 deletions
Download patch file Download diff file Expand all files Collapse all files

799
src/twaalgos/simulation.cc Normal file
View file

@ -0,0 +1,799 @@
// -*- coding: utf-8 -*-
// Copyright (C) 2012, 2013, 2014, 2015 Laboratoire de Recherche et
// Développement de l'Epita (LRDE).
//
// This file is part of Spot, a model checking library.
//
// Spot is free software; you can redistribute it and/or modify it
// under the terms of the GNU General Public License as published by
// the Free Software Foundation; either version 3 of the License, or
// (at your option) any later version.
//
// Spot is distributed in the hope that it will be useful, but WITHOUT
// ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
// or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
// License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
#include <queue>
#include <map>
#include <utility>
#include <cmath>
#include <limits>
#include "simulation.hh"
#include "misc/minato.hh"
#include "twa/bddprint.hh"
#include "twaalgos/reachiter.hh"
#include "twaalgos/sccfilter.hh"
#include "twaalgos/sccinfo.hh"
#include "misc/bddlt.hh"
// The way we developed this algorithm is the following: We take an
// automaton, and reverse all these acceptance conditions. We reverse
// them to go make the meaning of the signature easier. We are using
// bdd, and we want to let it make all the simplification. Because of
// the format of the acceptance condition, it doesn't allow easy
// simplification. Instead of encoding them as: "a!b!c + !ab!c", we
// use them as: "ab". We complement them because we want a
// simplification if the condition of the transition A implies the
// transition of B, and if the acceptance condition of A is included
// in the acceptance condition of B. To let the bdd makes the job, we
// revert them.
// Then, to check if a transition i-dominates another, we'll use the bdd:
// "sig(transA) = cond(trans) & acc(trans) & implied(class(trans->state))"
// Idem for sig(transB). The 'implied'
// (represented by a hash table 'relation_' in the implementation) is
// a conjunction of all the class dominated by the class of the
// destination. This is how the relation is included in the
// signature. It makes the simplifications alone, and the work is
// done. The algorithm is cut into several step:
//
// 1. Run through the tgba and switch the acceptance condition to their
// negation, and initializing relation_ by the 'init_ -> init_' where
// init_ is the bdd which represents the class. This function is the
// constructor of Simulation.
// 2. Enter in the loop (run).
// - Rename the class.
// - run through the automaton and computing the signature of each
// state. This function is `update_sig'.
// - Enter in a double loop to adapt the partial order, and set
// 'relation_' accordingly. This function is `update_po'.
// 3. Rename the class (to actualize the name in the previous_class and
// in relation_).
// 4. Building an automaton with the result, with the condition:
// "a transition in the original automaton appears in the simulated one
// iff this transition is included in the set of i-maximal neighbour."
// This function is `build_output'.
// The automaton simulated is recomplemented to come back to its initial
// state when the object Simulation is destroyed.
//
// Obviously these functions are possibly cut into several little ones.
// This is just the general development idea.
namespace spot
{
namespace
{
// Some useful typedef:
// Used to get the signature of the state.
typedef std::vector<bdd> vector_state_bdd;
// Get the list of state for each class.
typedef std::map<bdd, std::list<unsigned>,
bdd_less_than> map_bdd_lstate;
typedef std::map<bdd, unsigned, bdd_less_than> map_bdd_state;
// This class helps to compare two automata in term of
// size.
struct automaton_size
{
automaton_size()
: transitions(0),
states(0)
{
}
automaton_size(const twa_graph_ptr& a)
: transitions(a->num_transitions()),
states(a->num_states())
{
}
void set_size(const twa_graph_ptr& a)
{
states = a->num_states();
transitions = a->num_transitions();
}
inline bool operator!=(const automaton_size& r)
{
return transitions != r.transitions || states != r.states;
}
inline bool operator<(const automaton_size& r)
{
if (states < r.states)
return true;
if (states > r.states)
return false;
if (transitions < r.transitions)
return true;
if (transitions > r.transitions)
return false;
return false;
}
inline bool operator>(const automaton_size& r)
{
if (states < r.states)
return false;
if (states > r.states)
return true;
if (transitions < r.transitions)
return false;
if (transitions > r.transitions)
return true;
return false;
}
int transitions;
int states;
};
// The direct_simulation. If Cosimulation is true, we are doing a
// cosimulation.
template <bool Cosimulation, bool Sba>
class direct_simulation
{
protected:
// Shortcut used in update_po and go_to_next_it.
typedef std::map<bdd, bdd, bdd_less_than> map_bdd_bdd;
int acc_vars;
public:
bdd mark_to_bdd(acc_cond::mark_t m)
{
// FIXME: Use a cache.
bdd res = bddtrue;
for (auto n: a_->acc().sets(m))
res &= bdd_ithvar(acc_vars + n);
return res;
}
acc_cond::mark_t bdd_to_mark(const twa_graph_ptr& aut, bdd b)
{
// FIXME: Use a cache.
std::vector<unsigned> res;
while (b != bddtrue)
{
res.push_back(bdd_var(b) - acc_vars);
b = bdd_high(b);
}
return aut->acc().marks(res.begin(), res.end());
}
direct_simulation(const const_twa_graph_ptr& in)
: po_size_(0),
all_class_var_(bddtrue),
original_(in)
{
if (in->acc().uses_fin_acceptance())
throw std::runtime_error
("direct_simulation() does not yet support Fin acceptance");
// Call get_init_state_number() before anything else as it
// might add a state.
unsigned init_state_number = in->get_init_state_number();
scc_info_.reset(new scc_info(in));
unsigned ns = in->num_states();
assert(ns > 0);
size_a_ = ns;
// Replace all the acceptance conditions by their complements.
// (In the case of Cosimulation, we also flip the transitions.)
if (Cosimulation)
{
a_ = make_twa_graph(in->get_dict());
a_->copy_ap_of(in);
a_->copy_acceptance_of(in);
a_->new_states(ns);
auto& acccond = in->acc();
for (unsigned s = 0; s < ns; ++s)
{
for (auto& t: in->out(s))
{
acc_cond::mark_t acc;
if (Sba)
{
// If the acceptance is interpreted as
// state-based, to apply the reverse simulation
// on a SBA, we should pull the acceptance of
// the destination state on its incoming arcs
// (which now become outgoing arcs after
// transposition).
acc = 0U;
for (auto& td: in->out(t.dst))
{
acc = acccond.comp(td.acc);
break;
}
}
else
{
acc = acccond.comp(t.acc);
}
a_->new_transition(t.dst, s, t.cond, acc);
}
a_->set_init_state(init_state_number);
}
}
else
{
a_ = make_twa_graph(in, twa::prop_set::all());
auto& acccond = a_->acc();
for (auto& t: a_->transitions())
t.acc = acccond.comp(t.acc);
}
assert(a_->num_states() == size_a_);
// Now, we have to get the bdd which will represent the
// class. We register one bdd by state, because in the worst
// case, |Class| == |State|.
unsigned set_num = a_->get_dict()
->register_anonymous_variables(size_a_ + 1, this);
unsigned n_acc = a_->acc().num_sets();
acc_vars = a_->get_dict()
->register_anonymous_variables(n_acc, this);
all_proms_ = bddtrue;
for (unsigned v = acc_vars; v < acc_vars + n_acc; ++v)
all_proms_ &= bdd_ithvar(v);
bdd_initial = bdd_ithvar(set_num++);
bdd init = bdd_ithvar(set_num++);
used_var_.push_back(init);
// Initialize all classes to init.
previous_class_.resize(size_a_);
for (unsigned s = 0; s < size_a_; ++s)
previous_class_[s] = init;
// Put all the anonymous variable in a queue, and record all
// of these in a variable all_class_var_ which will be used
// to understand the destination part in the signature when
// building the resulting automaton.
all_class_var_ = init;
for (unsigned i = set_num; i < set_num + size_a_ - 1; ++i)
{
free_var_.push(i);
all_class_var_ &= bdd_ithvar(i);
}
relation_[init] = init;
}
// Reverse all the acceptance condition at the destruction of
// this object, because it occurs after the return of the
// function simulation.
virtual ~direct_simulation()
{
a_->get_dict()->unregister_all_my_variables(this);
}
// Update the name of the classes.
void update_previous_class()
{
std::list<bdd>::iterator it_bdd = used_var_.begin();
// We run through the map bdd/list<state>, and we update
// the previous_class_ with the new data.
for (auto& p: bdd_lstate_)
{
// If the signature of a state is bddfalse (no
// transitions) the class of this state is bddfalse
// instead of an anonymous variable. It allows
// simplifications in the signature by removing a
// transition which has as a destination a state with
// no outgoing transition.
if (p.first == bddfalse)
for (auto s: p.second)
previous_class_[s] = bddfalse;
else
for (auto s: p.second)
previous_class_[s] = *it_bdd;
++it_bdd;
}
}
void main_loop()
{
unsigned int nb_partition_before = 0;
unsigned int nb_po_before = po_size_ - 1;
while (nb_partition_before != bdd_lstate_.size()
|| nb_po_before != po_size_)
{
update_previous_class();
nb_partition_before = bdd_lstate_.size();
bdd_lstate_.clear();
nb_po_before = po_size_;
po_size_ = 0;
update_sig();
go_to_next_it();
}
update_previous_class();
}
// The core loop of the algorithm.
twa_graph_ptr run()
{
main_loop();
return build_result();
}
// Take a state and compute its signature.
bdd compute_sig(unsigned src)
{
bdd res = bddfalse;
for (auto& t: a_->out(src))
{
bdd acc = mark_to_bdd(t.acc);
// to_add is a conjunction of the acceptance condition,
// the label of the transition and the class of the
// destination and all the class it implies.
bdd to_add = acc & t.cond & relation_[previous_class_[t.dst]];
res |= to_add;
}
// When we Cosimulate, we add a special flag to differentiate
// the initial state from the other.
if (Cosimulation && src == a_->get_init_state_number())
res |= bdd_initial;
return res;
}
void update_sig()
{
for (unsigned s = 0; s < size_a_; ++s)
bdd_lstate_[compute_sig(s)].push_back(s);
}
// This method rename the color set, update the partial order.
void go_to_next_it()
{
int nb_new_color = bdd_lstate_.size() - used_var_.size();
// If we have created more partitions, we need to use more
// variables.
for (int i = 0; i < nb_new_color; ++i)
{
assert(!free_var_.empty());
used_var_.push_back(bdd_ithvar(free_var_.front()));
free_var_.pop();
}
// If we have reduced the number of partition, we 'free' them
// in the free_var_ list.
for (int i = 0; i > nb_new_color; --i)
{
assert(!used_var_.empty());
free_var_.push(bdd_var(used_var_.front()));
used_var_.pop_front();
}
assert((bdd_lstate_.size() == used_var_.size())
|| (bdd_lstate_.find(bddfalse) != bdd_lstate_.end()
&& bdd_lstate_.size() == used_var_.size() + 1));
// Now we make a temporary hash_table which links the tuple
// "C^(i-1), N^(i-1)" to the new class coloring. If we
// rename the class before updating the partial order, we
// loose the information, and if we make it after, I can't
// figure out how to apply this renaming on rel_.
// It adds a data structure but it solves our problem.
map_bdd_bdd now_to_next;
std::list<bdd>::iterator it_bdd = used_var_.begin();
for (auto& p: bdd_lstate_)
{
// If the signature of a state is bddfalse (no
// transitions) the class of this state is bddfalse
// instead of an anonymous variable. It allows
// simplifications in the signature by removing a
// transition which has as a destination a state with
// no outgoing transition.
bdd acc = bddfalse;
if (p.first != bddfalse)
acc = *it_bdd;
now_to_next[p.first] = acc;
++it_bdd;
}
update_po(now_to_next, relation_);
}
// This function computes the new po with previous_class_ and
// the argument. `now_to_next' contains the relation between the
// signature and the future name of the class. We need a
// template parameter because we use this function with a
// map_bdd_bdd, but later, we need a list_bdd_bdd. So to
// factorize some code we use a template.
template <typename container_bdd_bdd>
void update_po(const container_bdd_bdd& now_to_next,
map_bdd_bdd& relation)
{
// This loop follows the pattern given by the paper.
// foreach class do
// | foreach class do
// | | update po if needed
// | od
// od
for (typename container_bdd_bdd::const_iterator it1
= now_to_next.begin();
it1 != now_to_next.end();
++it1)
{
bdd accu = it1->second;
for (typename container_bdd_bdd::const_iterator it2
= now_to_next.begin();
it2 != now_to_next.end();
++it2)
{
// Skip the case managed by the initialization of accu.
if (it1 == it2)
continue;
if (bdd_implies(it1->first, it2->first))
{
accu &= it2->second;
++po_size_;
}
}
relation[it1->second] = accu;
}
}
// Build the minimal resulting automaton.
twa_graph_ptr build_result()
{
twa_graph_ptr res = make_twa_graph(a_->get_dict());
res->copy_ap_of(a_);
res->copy_acceptance_of(a_);
if (Sba)
res->prop_state_based_acc();
// Non atomic propositions variables (= acc and class)
bdd nonapvars = all_proms_ & bdd_support(all_class_var_);
auto* gb = res->create_namer<int>();
// Create one state per partition.
for (auto& p: bdd_lstate_)
{
bdd cl = previous_class_[p.second.front()];
// A state may be referred to either by
// its class, or by all the implied classes.
auto s = gb->new_state(cl.id());
gb->alias_state(s, relation_[cl].id());
}
// Acceptance of states. Only used if Sba && Cosimulation.
std::vector<acc_cond::mark_t> accst;
if (Sba && Cosimulation)
accst.resize(res->num_states(), 0U);
stat.states = bdd_lstate_.size();
stat.transitions = 0;
unsigned nb_satoneset = 0;
unsigned nb_minato = 0;
// For each class, we will create
// all the transitions between the states.
for (auto& p: bdd_lstate_)
{
// All states in p.second have the same class, so just
// pick the class of the first one first one.
bdd src = previous_class_[p.second.front()];
// Get the signature to derive successors.
bdd sig = compute_sig(p.second.front());
if (Cosimulation)
sig = bdd_compose(sig, bddfalse, bdd_var(bdd_initial));
// Get all the variable in the signature.
bdd sup_sig = bdd_support(sig);
// Get the variable in the signature which represents the
// conditions.
bdd sup_all_atomic_prop = bdd_exist(sup_sig, nonapvars);
// Get the part of the signature composed only with the atomic
// proposition.
bdd all_atomic_prop = bdd_exist(sig, nonapvars);
// First loop over all possible valuations atomic properties.
while (all_atomic_prop != bddfalse)
{
bdd one = bdd_satoneset(all_atomic_prop,
sup_all_atomic_prop,
bddtrue);
all_atomic_prop -= one;
// For each possible valuation, iterate over all possible
// destination classes. We use minato_isop here, because
// if the same valuation of atomic properties can go
// to two different classes C1 and C2, iterating on
// C1 + C2 with the above bdd_satoneset loop will see
// C1 then (!C1)C2, instead of C1 then C2.
// With minatop_isop, we ensure that the no negative
// class variable will be seen (likewise for promises).
minato_isop isop(sig & one);
++nb_satoneset;
bdd cond_acc_dest;
while ((cond_acc_dest = isop.next()) != bddfalse)
{
++stat.transitions;
++nb_minato;
// Take the transition, and keep only the variable which
// are used to represent the class.
bdd dst = bdd_existcomp(cond_acc_dest,
all_class_var_);
// Keep only ones who are acceptance condition.
auto acc = bdd_to_mark(res, bdd_existcomp(cond_acc_dest,
all_proms_));
// Keep the other!
bdd cond = bdd_existcomp(cond_acc_dest,
sup_all_atomic_prop);
// Because we have complemented all the acceptance
// conditions on the input automaton, we must
// revert them to create a new transition.
acc = res->acc().comp(acc);
if (Cosimulation)
{
if (Sba)
{
// acc should be attached to src, or rather,
// in our transition-based representation)
// to all transitions leaving src. As we
// can't do this here, store this in a table
// so we can fix it later.
accst[gb->get_state(src.id())] = acc;
acc = 0U;
}
gb->new_transition(dst.id(), src.id(), cond, acc);
}
else
{
gb->new_transition(src.id(), dst.id(), cond, acc);
}
}
}
}
res->set_init_state(gb->get_state(previous_class_
[a_->get_init_state_number()].id()));
res->merge_transitions(); // FIXME: is this really needed?
// Mark all accepting state in a second pass, when
// dealing with SBA in cosimulation.
if (Sba && Cosimulation)
{
unsigned ns = res->num_states();
for (unsigned s = 0; s < ns; ++s)
{
acc_cond::mark_t acc = accst[s];
if (acc == 0U)
continue;
for (auto& t: res->out(s))
t.acc = acc;
}
}
res->purge_unreachable_states();
delete gb;
res->prop_copy(original_,
{ false, // state-based acc forced below
true, // weakness preserved,
false, // determinism checked and set below
true, // stutter inv.
});
if (nb_minato == nb_satoneset && !Cosimulation)
res->prop_deterministic();
if (Sba)
res->prop_state_based_acc();
return res;
}
// Debug:
// In a first time, print the signature, and the print a list
// of each state in this partition.
// In a second time, print foreach state, who is where,
// where is the new class name.
void print_partition()
{
for (auto& p: bdd_lstate_)
{
std::cerr << "partition: "
<< bdd_format_isop(a_->get_dict(), p.first)
<< std::endl;
for (auto s: p.second)
std::cerr << " - "
<< a_->format_state(a_->state_from_number(s))
<< '\n';
}
std::cerr << "\nPrevious iteration\n" << std::endl;
unsigned ps = previous_class_.size();
for (unsigned p = 0; p < ps; ++p)
{
std::cerr << a_->format_state(a_->state_from_number(p))
<< " was in "
<< bdd_format_set(a_->get_dict(), previous_class_[p])
<< '\n';
}
}
protected:
// The automaton which is simulated.
twa_graph_ptr a_;
// Relation is aimed to represent the same thing than
// rel_. The difference is in the way it does.
// If A => A /\ A => B, rel will be (!A U B), but relation_
// will have A /\ B at the key A. This trick is due to a problem
// with the computation of the resulting automaton with the signature.
// rel_ will pollute the meaning of the signature.
map_bdd_bdd relation_;
// Represent the class of each state at the previous iteration.
vector_state_bdd previous_class_;
// The list of state for each class at the current_iteration.
// Computed in `update_sig'.
map_bdd_lstate bdd_lstate_;
// The queue of free bdd. They will be used as the identifier
// for the class.
std::queue<int> free_var_;
// The list of used bdd. They are in used as identifier for class.
std::list<bdd> used_var_;
// Size of the automaton.
unsigned int size_a_;
// Used to know when there is no evolution in the po. Updated
// in the `update_po' method.
unsigned int po_size_;
// All the class variable:
bdd all_class_var_;
// The flag to say if the outgoing state is initial or not
bdd bdd_initial;
bdd all_proms_;
automaton_size stat;
std::unique_ptr<scc_info> scc_info_;
const const_twa_graph_ptr original_;
};
} // End namespace anonymous.
twa_graph_ptr
simulation(const const_twa_graph_ptr& t)
{
direct_simulation<false, false> simul(t);
return simul.run();
}
twa_graph_ptr
simulation_sba(const const_twa_graph_ptr& t)
{
direct_simulation<false, true> simul(t);
return simul.run();
}
twa_graph_ptr
cosimulation(const const_twa_graph_ptr& t)
{
direct_simulation<true, false> simul(t);
return simul.run();
}
twa_graph_ptr
cosimulation_sba(const const_twa_graph_ptr& t)
{
direct_simulation<true, true> simul(t);
return simul.run();
}
template<bool Sba>
twa_graph_ptr
iterated_simulations_(const const_twa_graph_ptr& t)
{
twa_graph_ptr res = 0;
automaton_size prev;
automaton_size next;
do
{
prev = next;
direct_simulation<false, Sba> simul(res ? res : t);
res = simul.run();
if (res->is_deterministic())
break;
direct_simulation<true, Sba> cosimul(res);
res = cosimul.run();
if (Sba)
res = scc_filter_states(res);
else
res = scc_filter(res, false);
next.set_size(res);
}
while (prev != next);
return res;
}
twa_graph_ptr
iterated_simulations(const const_twa_graph_ptr& t)
{
return iterated_simulations_<false>(t);
}
twa_graph_ptr
iterated_simulations_sba(const const_twa_graph_ptr& t)
{
return iterated_simulations_<true>(t);
}
} // End namespace spot.