71f1928052
* spot/twaalgos/degen.cc, spot/twaalgos/degen.hh (propagate_marks_vector, propagate_marks_here): Take the scc_info* argument as const.
181 lines
7.7 KiB
C++
181 lines
7.7 KiB
C++
// -*- coding: utf-8 -*-
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// Copyright (C) 2012-2015, 2017-2020 Laboratoire de
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// Recherche et Développement de l'Epita.
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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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#pragma once
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#include <spot/twa/twagraph.hh>
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namespace spot
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{
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class scc_info;
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/// \ingroup twa_acc_transform
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/// \brief Degeneralize a spot::tgba into an equivalent sba with
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/// only one acceptance condition.
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///
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/// This algorithm will build a new explicit automaton that has
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/// at most (N+1) times the number of states of the original automaton.
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///
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/// When \a use_z_lvl is set, the level of the degeneralized
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/// automaton is reset everytime an SCC is exited. If \a
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/// use_cust_acc_orders is set, the degeneralization will compute a
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/// custom acceptance order for each SCC (this option is disabled by
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/// default because our benchmarks show that it usually does more
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/// harm than good). If \a use_lvl_cache is set, everytime an SCC
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/// is entered on a state that as already been associated to some
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/// level elsewhere, reuse that level (set it to 2 to keep the
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/// smallest number, 3 to keep the largest level, and 1 to keep the
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/// first level found). If \a ignaccsl is set, we do not directly
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/// jump to the accepting level if the entering state has an
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/// accepting self-loop. If \a remove_extra_scc is set (the default)
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/// we ensure that the output automaton has as many SCCs as the input
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/// by removing superfluous SCCs.
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///
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/// Any of these three options will cause the SCCs of the automaton
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/// \a a to be computed prior to its actual degeneralization.
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///
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/// The degeneralize_tba() variant produce a degeneralized automaton
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/// with transition-based acceptance.
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///
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/// The mapping between each state of the resulting automaton
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/// and the original state of the input automaton is stored in the
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/// "original-states" named property of the produced automaton. Call
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/// `aut->get_named_prop<std::vector<unsigned>>("original-states")`
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/// to retrieve it. However be aware that if the input automaton
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/// already defines the "original-states" named property, it will
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/// be composed with the new one, so the "original-states" of the
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/// degeneralized automaton will refer to the same automaton as the
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/// "original-states" of the input automaton.
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///
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/// Note that these functions may return the original
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/// automaton as-is if it is already degeneralized; in this case
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/// the "original-states" property is not defined (or not changed).
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///
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/// Similarly, the property "degen-levels" keeps track of the degeneralization
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/// levels. To retrieve it, call
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/// `aut->get_named_prop<std::vector<unsigned>>("degen-levels")`.
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/// \@{
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SPOT_API twa_graph_ptr
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degeneralize(const const_twa_graph_ptr& a, bool use_z_lvl = true,
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bool use_cust_acc_orders = false,
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int use_lvl_cache = 1,
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bool skip_levels = true,
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bool ignaccsl = false,
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bool remove_extra_scc = true);
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SPOT_API twa_graph_ptr
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degeneralize_tba(const const_twa_graph_ptr& a, bool use_z_lvl = true,
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bool use_cust_acc_orders = false,
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int use_lvl_cache = 1,
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bool skip_levels = true,
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bool ignaccsl = false,
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bool remove_extra_scc = true);
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/// \@}
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/// \ingroup twa_acc_transform
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/// \brief Partial degeneralization of a TwA
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///
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/// Given an automaton whose acceptance contains a conjunction of
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/// Inf terms, perform a partial degeneralization to replace this
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/// conjunction by a single Inf term.
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///
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/// For instance if the input has acceptance
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/// (Fin(0)&Inf(1)&Inf(3))|Fin(2)
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/// calling partial_degeneralize with \a todegen set to `{1,3}`
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/// will build an equivalent automaton with acceptance
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/// (Fin(0)&Inf(2))|Fin(1)
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///
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/// where Inf(2) tracks the acceptance of the original
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/// Inf(1)&Inf(3), and Fin(1) tracks the acceptance of the original
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/// Fin(2).
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///
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/// Cases where the sets listed in \a todegen also occur outside
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/// of the Inf-conjunction are also supported. Subformulas that
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/// are disjunctions of Fin(.) terms (e.g., Fin(1)|Fin(2)) will
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/// be degeneralized as well.
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///
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/// If this functions is called with a value of \a todegen that does
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/// not match a conjunction of Inf(.), or a disjunction of Fin(.),
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/// an std::runtime_error exception is thrown.
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///
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/// The version of the function that has no \a todegen argument will
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/// perform all possible partial degeneralizations, and may return
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/// the input automaton unmodified if no partial degeneralization is
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/// possible.
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///
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/// The "original-state" and "degen-levels" named properties are
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/// updated as for degeneralize() and degeneralize_tba().
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/// @{
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SPOT_API twa_graph_ptr
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partial_degeneralize(const const_twa_graph_ptr& a,
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acc_cond::mark_t todegen);
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SPOT_API twa_graph_ptr
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partial_degeneralize(twa_graph_ptr a);
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/// @}
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/// \brief Is the automaton partially degeneralizable?
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///
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/// Return a mark `M={m₁, m₂, ..., mₙ}` such that either
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/// `Inf(m₁)&Inf(m₂)&...&Inf(mₙ)` or `Fin(m₁)|Fin(m₂)|...|Fin(mₙ)`
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/// appears in the acceptance condition of \a aut.
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///
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/// If multiple such marks exist the smallest such mark is returned.
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/// (This is important in case of overlapping options. E.g., in the
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/// formula `Inf(0)&Inf(1)&Inf(3) | (Inf(0)&Inf(1))&Fin(2)` we have
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/// two possible degeneralizations options `{0,1,3}`, and `{0,1}`.
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/// Degeneralizing for `{0,1,3}` and then `{0,1}` could enlarge the
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/// automaton by a factor 6, while degeneralizing by `{0,1}` and
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/// then some `{x,y}` may enlarge the automaton only by a factor 4.)
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///
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/// Return an empty mark otherwise if the automaton is not partially
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/// degeneralizable.
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///
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/// The optional arguments \a allow_inf and \a allow_fin, can be set
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/// to false to disallow one type of match.
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SPOT_API acc_cond::mark_t
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is_partially_degeneralizable(const const_twa_graph_ptr& aut,
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bool allow_inf = true,
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bool allow_fin = true,
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std::vector<acc_cond::mark_t> forbid = {});
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/// \ingroup twa_algorithms
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/// \brief Propagate marks around the automaton
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///
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/// For each state of the automaton, marks that are common
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/// to all input transitions will be pushed on the outgoing
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/// transitions, and marks that are common to all outgoing
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/// transitions will be pulled to the input transitions.
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/// This considers only transitions that are not self-loops
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/// and that belong to some SCC. If an scc_info has already
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/// been built, pass it as \a si to avoid building it again.
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///
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/// Two variants of the algorithm are provided. One modifies
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/// the automaton in place; the second returns a vector of marks
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/// indexed by transition numbers.
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///
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/// @{
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SPOT_API std::vector<acc_cond::mark_t>
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propagate_marks_vector(const const_twa_graph_ptr& aut,
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const scc_info* si = nullptr);
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SPOT_API void
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propagate_marks_here(twa_graph_ptr& aut,
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const scc_info* si = nullptr);
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/// @}
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}
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