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to_parity: improve doc, and rename car_option into to_parity_options

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* spot/twaalgos/toparity.hh: Improve doc, and rename car_option into
to_parity_options.
* doc/spot.bib: Add one reference.
* python/spot/__init__.py, spot/twaalgos/toparity.cc,
tests/python/toparity.py: Adjust.
This commit is contained in:
Alexandre Duret-Lutz 2020-04-04 14:43:47 +02:00
parent 86144ac171
commit 1750c0fb6d
5 changed files with 97 additions and 60 deletions
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8
spot/twaalgos/toparity.cc
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@ -1,5 +1,5 @@
// -*- coding: utf-8 -*-
// Copyright (C) 2018, 2019 Laboratoire de Recherche et Développement
// Copyright (C) 2018-2020 Laboratoire de Recherche et Développement
// de l'Epita.
//
// This file is part of Spot, a model checking library.
@ -799,7 +799,7 @@ get_iar_to_vector(const twa_graph_ptr& aut, algorithm algo,
}
public:
explicit car_generator(const const_twa_graph_ptr &a, car_option options)
explicit car_generator(const const_twa_graph_ptr &a, to_parity_options options)
: aut_(a)
, scc_(scc_info(a))
, is_odd(false)
@ -1600,7 +1600,7 @@ std::vector<car_state> num2car;
std::map<unsigned, car_state> state2car;
std::map<car_state, unsigned> car2num;
car_option options;
to_parity_options options;
std::vector<std::string>* names;
}; // car_generator
@ -1624,7 +1624,7 @@ remove_false_transitions(const twa_graph_ptr a)
}
twa_graph_ptr
to_parity(const twa_graph_ptr &aut, const car_option options)
to_parity(const twa_graph_ptr &aut, const to_parity_options options)
{
return car_generator(remove_false_transitions(aut), options).run();
}

114
spot/twaalgos/toparity.hh
View file

@ -1,5 +1,5 @@
// -*- coding: utf-8 -*-
// Copyright (C) 2012-2020 Laboratoire de Recherche et Développement
// Copyright (C) 2018-2020 Laboratoire de Recherche et Développement
// de l'Epita (LRDE).
//
// This file is part of Spot, a model checking library.
@ -23,81 +23,101 @@
namespace spot
{
// The version that combines CAR, IAR and multiple optimizations.
struct car_option
{
bool search_ex = true;
bool use_last = true;
bool force_order = true;
bool partial_degen = true;
bool acc_clean = true;
bool parity_equiv = true;
bool parity_prefix = true;
bool rabin_to_buchi = true;
bool reduce_col_deg = false;
bool propagate_col = true;
bool pretty_print = false;
};
/// \ingroup twa_acc_transform
/// \brief Options to control various optimizations of to_parity().
struct to_parity_options
{
/// If \c search_ex is true, whenever CAR or IAR have to move
/// several elements in a record, it tries to find an order such
/// that the new permutation already exists.
bool search_ex = true;
/// If \a use_last is true and \a search_ex are true, we use the
/// most recent state when we find multiple existing state
/// compatible with the current move.
bool use_last = true;
bool force_order = true;
/// If \c partial_degen is true, apply a partial
/// degeneralization to remove occurrences of acceptance
/// subformulas such as `Fin(x) | Fin(y)` or `Inf(x) & Inf(y)`.
bool partial_degen = true;
/// If \c scc_acc_clean is true, to_parity() will ignore colors
/// no occoring in an SCC while processing this SCC.
bool acc_clean = true;
/// If \a parity_equiv is true, to_parity() will check if there
/// exists a permutations of colors such that the acceptance
/// condition is a parity condition.
bool parity_equiv = true;
bool parity_prefix = true;
bool rabin_to_buchi = true;
bool reduce_col_deg = false;
bool propagate_col = true;
/// If \a pretty_print is true, states of the output automaton are
/// named to help debugging.
bool pretty_print = false;
};
/// \ingroup twa_acc_transform
/// \brief Take an automaton with any acceptance condition and return an
/// equivalent parity automaton.
///
/// The parity condition of the returned automaton is max even or
/// max odd.
/// If \a search_ex is true, when we move several elements, we
/// try to find an order such that the new permutation already exists.
/// If \a partial_degen is true, we apply a partial degeneralization to remove
// occurences of Fin | Fin and Inf & Inf.
/// If \a scc_acc_clean is true, we remove for each SCC the colors that don't
// appear.
/// If \a parity_equiv is true, we check if there exists a permutations of
// colors such that the acceptance
/// condition is a partity condition.
/// If \a use_last is true, we use the most recent state when looking for an
// existing state.
/// If \a pretty_print is true, we give a name to the states describing the
// state of the aut_ and the permutation.
/// \ingroup twa_acc_transform
/// \brief Take an automaton with any acceptance condition and return an
/// equivalent parity automaton.
///
/// The parity condition of the returned automaton is either max even or
/// max odd.
///
/// This procedure combines many strategies in an attempt to produce
/// the smallest possible parity automaton. Some of the strategies
/// include CAR (color acceptance record), IAR (index appearance
/// record), partial degenerazation, conversion from Rabin to Büchi
/// when possible, etc.
///
/// The \a options argument can be used to selectively disable some of the
/// optimizations.
SPOT_API twa_graph_ptr
to_parity(const twa_graph_ptr &aut,
const to_parity_options options = to_parity_options());
SPOT_API twa_graph_ptr
remove_false_transitions(const twa_graph_ptr a);
SPOT_API twa_graph_ptr
to_parity(const twa_graph_ptr &aut, const car_option options = car_option());
// Old version of CAR
/// \ingroup twa_acc_transform
/// \brief Take an automaton with any acceptance condition and return an
/// equivalent parity automaton.
///
/// The parity condition of the returned automaton is max even.
///
/// This implements a straightforward adaptation of the LAR (latest
/// appearance record) to automata with transition-based marks. We
/// call this adaptation the CAR (color apperance record), as it
/// tracks colors (i.e., acceptance sets) instead of states.
///
/// It is better to use to_parity() instead, as it will use better
/// strategies when possible, and has additional optimizations.
SPOT_API twa_graph_ptr
to_parity_old(const const_twa_graph_ptr& aut, bool pretty_print=false);
// Old version of IAR
/// \ingroup twa_acc_transform
/// \brief Turn a Rabin-like or Streett-like automaton into a parity automaton
/// based on the index appearence record (IAR)
///
/// This is an implementation of \cite kretinsky.17.tacas .
/// If the input automaton has n states and k pairs, the output automaton has
/// at most k!*n states and 2k+1 colors. If the input automaton is
/// deterministic, the output automaton is deterministic as well, which is the
/// intended use case for this function. If the input automaton is
/// non-deterministic, the result is still correct, but way larger than an
/// equivalent Büchi automaton.
///
/// If the input automaton is Rabin-like (resp. Streett-like), the output
/// automaton has max odd (resp. min even) acceptance condition.
/// Details on the algorithm can be found in:
/// https://arxiv.org/pdf/1701.05738.pdf (published at TACAS 2017)
///
/// Throws an std::runtime_error if the input is neither Rabin-like nor
/// Street-like.
SPOT_API
twa_graph_ptr
///
/// It is better to use to_parity() instead, as it will use better
/// strategies when possible, and has additional optimizations.
SPOT_API twa_graph_ptr
iar_old(const const_twa_graph_ptr& aut, bool pretty_print = false);
/// \ingroup twa_acc_transform
@ -105,9 +125,9 @@ namespace spot
/// based on the index appearence record (IAR)
///
/// Returns nullptr if the input automaton is neither Rabin-like nor
/// Streett-like, and calls spot::iar() otherwise.
/// Streett-like, and calls spot::iar_old() otherwise.
SPOT_API
twa_graph_ptr
iar_maybe_old(const const_twa_graph_ptr& aut, bool pretty_print = false);
} // namespace spot
} // namespace spot