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yap-6.3/packages/swi-minisat2/C/Solver.h

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/****************************************************************************************[Solver.h]
MiniSat -- Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and
associated documentation files (the "Software"), to deal in the Software without restriction,
including without limitation the rights to use, copy, modify, merge, publish, distribute,
sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or
substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT
OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
**************************************************************************************************/
#ifndef Solver_h
#define Solver_h
#include <cstdio>
#include "Vec.h"
#include "Heap.h"
#include "Alg.h"
#include "SolverTypes.h"
//=================================================================================================
// Solver -- the main class:
class Solver {
public:
// Constructor/Destructor:
//
Solver();
~Solver();
// Problem specification:
//
Var newVar (bool polarity = true, bool dvar = true); // Add a new variable with parameters specifying variable mode.
bool addClause (vec<Lit>& ps); // Add a clause to the solver. NOTE! 'ps' may be shrunk by this method!
bool setminVars(vec<Lit>& ps);
// Solving:
//
bool simplify (); // Removes already satisfied clauses.
bool solve (const vec<Lit>& assumps); // Search for a model that respects a given set of assumptions.
bool solve (); // Search without assumptions.
bool okay () const; // FALSE means solver is in a conflicting state
// Variable mode:
//
void setPolarity (Var v, bool b); // Declare which polarity the decision heuristic should use for a variable. Requires mode 'polarity_user'.
void setDecisionVar (Var v, bool b); // Declare if a variable should be eligible for selection in the decision heuristic.
// Read state:
//
lbool value (Var x) const; // The current value of a variable.
lbool value (Lit p) const; // The current value of a literal.
lbool modelValue (Lit p) const; // The value of a literal in the last model. The last call to solve must have been satisfiable.
int nAssigns () const; // The current number of assigned literals.
int nClauses () const; // The current number of original clauses.
int nLearnts () const; // The current number of learnt clauses.
int nVars () const; // The current number of variables.
// Extra results: (read-only member variable)
//
vec<lbool> model; // If problem is satisfiable, this vector contains the model (if any).
vec<Lit> conflict; // If problem is unsatisfiable (possibly under assumptions),
// this vector represent the final conflict clause expressed in the assumptions.
// Mode of operation:
//
double var_decay; // Inverse of the variable activity decay factor. (default 1 / 0.95)
double clause_decay; // Inverse of the clause activity decay factor. (1 / 0.999)
double random_var_freq; // The frequency with which the decision heuristic tries to choose a random variable. (default 0.02)
int restart_first; // The initial restart limit. (default 100)
double restart_inc; // The factor with which the restart limit is multiplied in each restart. (default 1.5)
double learntsize_factor; // The intitial limit for learnt clauses is a factor of the original clauses. (default 1 / 3)
double learntsize_inc; // The limit for learnt clauses is multiplied with this factor each restart. (default 1.1)
bool expensive_ccmin; // Controls conflict clause minimization. (default TRUE)
int polarity_mode; // Controls which polarity the decision heuristic chooses. See enum below for allowed modes. (default polarity_false)
int verbosity; // Verbosity level. 0=silent, 1=some progress report (default 0)
enum { polarity_true = 0, polarity_false = 1, polarity_user = 2, polarity_rnd = 3 };
// Statistics: (read-only member variable)
//
uint64_t starts, decisions, rnd_decisions, propagations, conflicts;
uint64_t clauses_literals, learnts_literals, max_literals, tot_literals;
protected:
// Helper structures:
//
struct VarOrderLt {
const vec<double>& activity;
bool operator () (Var x, Var y) const { return activity[x] > activity[y]; }
VarOrderLt(const vec<double>& act) : activity(act) { }
};
friend class VarFilter;
struct VarFilter {
const Solver& s;
VarFilter(const Solver& _s) : s(_s) {}
bool operator()(Var v) const { return toLbool(s.assigns[v]) == l_Undef && s.decision_var[v]; }
};
// Solver state:
//
//****************
bool allMinVarsAssigned;
int lastMinVarDL;
vec<Lit> minVars;
//****************
bool ok; // If FALSE, the constraints are already unsatisfiable. No part of the solver state may be used!
vec<Clause*> clauses; // List of problem clauses.
vec<Clause*> learnts; // List of learnt clauses.
double cla_inc; // Amount to bump next clause with.
vec<double> activity; // A heuristic measurement of the activity of a variable.
double var_inc; // Amount to bump next variable with.
vec<vec<Clause*> > watches; // 'watches[lit]' is a list of constraints watching 'lit' (will go there if literal becomes true).
vec<char> assigns; // The current assignments (lbool:s stored as char:s).
vec<char> polarity; // The preferred polarity of each variable.
vec<char> decision_var; // Declares if a variable is eligible for selection in the decision heuristic.
vec<Lit> trail; // Assignment stack; stores all assigments made in the order they were made.
vec<int> trail_lim; // Separator indices for different decision levels in 'trail'.
vec<Clause*> reason; // 'reason[var]' is the clause that implied the variables current value, or 'NULL' if none.
vec<int> level; // 'level[var]' contains the level at which the assignment was made.
int qhead; // Head of queue (as index into the trail -- no more explicit propagation queue in MiniSat).
int simpDB_assigns; // Number of top-level assignments since last execution of 'simplify()'.
int64_t simpDB_props; // Remaining number of propagations that must be made before next execution of 'simplify()'.
vec<Lit> assumptions; // Current set of assumptions provided to solve by the user.
Heap<VarOrderLt> order_heap; // A priority queue of variables ordered with respect to the variable activity.
double random_seed; // Used by the random variable selection.
double progress_estimate;// Set by 'search()'.
bool remove_satisfied; // Indicates whether possibly inefficient linear scan for satisfied clauses should be performed in 'simplify'.
// Temporaries (to reduce allocation overhead). Each variable is prefixed by the method in which it is
// used, exept 'seen' wich is used in several places.
//
vec<char> seen;
vec<Lit> analyze_stack;
vec<Lit> analyze_toclear;
vec<Lit> add_tmp;
// Main internal methods:
//
void insertVarOrder (Var x); // Insert a variable in the decision order priority queue.
Lit pickBranchLit (int polarity_mode, double random_var_freq); // Return the next decision variable.
void newDecisionLevel (); // Begins a new decision level.
void uncheckedEnqueue (Lit p, Clause* from = NULL); // Enqueue a literal. Assumes value of literal is undefined.
bool enqueue (Lit p, Clause* from = NULL); // Test if fact 'p' contradicts current state, enqueue otherwise.
Clause* propagate (); // Perform unit propagation. Returns possibly conflicting clause.
void cancelUntil (int level); // Backtrack until a certain level.
void analyze (Clause* confl, vec<Lit>& out_learnt, int& out_btlevel); // (bt = backtrack)
void analyzeFinal (Lit p, vec<Lit>& out_conflict); // COULD THIS BE IMPLEMENTED BY THE ORDINARIY "analyze" BY SOME REASONABLE GENERALIZATION?
bool litRedundant (Lit p, uint32_t abstract_levels); // (helper method for 'analyze()')
lbool search (int nof_conflicts, int nof_learnts); // Search for a given number of conflicts.
void reduceDB (); // Reduce the set of learnt clauses.
void removeSatisfied (vec<Clause*>& cs); // Shrink 'cs' to contain only non-satisfied clauses.
// Maintaining Variable/Clause activity:
//
void varDecayActivity (); // Decay all variables with the specified factor. Implemented by increasing the 'bump' value instead.
void varBumpActivity (Var v); // Increase a variable with the current 'bump' value.
void claDecayActivity (); // Decay all clauses with the specified factor. Implemented by increasing the 'bump' value instead.
void claBumpActivity (Clause& c); // Increase a clause with the current 'bump' value.
// Operations on clauses:
//
void attachClause (Clause& c); // Attach a clause to watcher lists.
void detachClause (Clause& c); // Detach a clause to watcher lists.
void removeClause (Clause& c); // Detach and free a clause.
bool locked (const Clause& c) const; // Returns TRUE if a clause is a reason for some implication in the current state.
bool satisfied (const Clause& c) const; // Returns TRUE if a clause is satisfied in the current state.
// Misc:
//
int decisionLevel () const; // Gives the current decisionlevel.
uint32_t abstractLevel (Var x) const; // Used to represent an abstraction of sets of decision levels.
double progressEstimate () const; // DELETE THIS ?? IT'S NOT VERY USEFUL ...
// Debug:
void printLit (Lit l);
template<class C>
void printClause (const C& c);
void verifyModel ();
void checkLiteralCount();
// Static helpers:
//
// Returns a random float 0 <= x < 1. Seed must never be 0.
static inline double drand(double& seed) {
seed *= 1389796;
int q = (int)(seed / 2147483647);
seed -= (double)q * 2147483647;
return seed / 2147483647; }
// Returns a random integer 0 <= x < size. Seed must never be 0.
static inline int irand(double& seed, int size) {
return (int)(drand(seed) * size); }
};
//=================================================================================================
// Implementation of inline methods:
inline void Solver::insertVarOrder(Var x) {
if (!order_heap.inHeap(x) && decision_var[x]) order_heap.insert(x); }
inline void Solver::varDecayActivity() { var_inc *= var_decay; }
inline void Solver::varBumpActivity(Var v) {
if ( (activity[v] += var_inc) > 1e100 ) {
// Rescale:
for (int i = 0; i < nVars(); i++)
activity[i] *= 1e-100;
var_inc *= 1e-100; }
// Update order_heap with respect to new activity:
if (order_heap.inHeap(v))
order_heap.decrease(v); }
inline void Solver::claDecayActivity() { cla_inc *= clause_decay; }
inline void Solver::claBumpActivity (Clause& c) {
if ( (c.activity() += cla_inc) > 1e20 ) {
// Rescale:
for (int i = 0; i < learnts.size(); i++)
learnts[i]->activity() *= 1e-20;
cla_inc *= 1e-20; } }
inline bool Solver::enqueue (Lit p, Clause* from) { return value(p) != l_Undef ? value(p) != l_False : (uncheckedEnqueue(p, from), true); }
inline bool Solver::locked (const Clause& c) const { return reason[var(c[0])] == &c && value(c[0]) == l_True; }
inline void Solver::newDecisionLevel() { trail_lim.push(trail.size()); }
inline int Solver::decisionLevel () const { return trail_lim.size(); }
inline uint32_t Solver::abstractLevel (Var x) const { return 1 << (level[x] & 31); }
inline lbool Solver::value (Var x) const { return toLbool(assigns[x]); }
inline lbool Solver::value (Lit p) const { return toLbool(assigns[var(p)]) ^ sign(p); }
inline lbool Solver::modelValue (Lit p) const { return model[var(p)] ^ sign(p); }
inline int Solver::nAssigns () const { return trail.size(); }
inline int Solver::nClauses () const { return clauses.size(); }
inline int Solver::nLearnts () const { return learnts.size(); }
inline int Solver::nVars () const { return assigns.size(); }
inline void Solver::setPolarity (Var v, bool b) { polarity [v] = (char)b; }
inline void Solver::setDecisionVar(Var v, bool b) { decision_var[v] = (char)b; if (b) { insertVarOrder(v); } }
inline bool Solver::solve () { vec<Lit> tmp; return solve(tmp); }
inline bool Solver::okay () const { return ok; }
//=================================================================================================
// Debug + etc:
#define reportf(format, args...) ( fflush(stdout), fprintf(stderr, format, ## args), fflush(stderr) )
static inline void logLit(FILE* f, Lit l)
{
fprintf(f, "%sx%d", sign(l) ? "~" : "", var(l)+1);
}
static inline void logLits(FILE* f, const vec<Lit>& ls)
{
fprintf(f, "[ ");
if (ls.size() > 0){
logLit(f, ls[0]);
for (int i = 1; i < ls.size(); i++){
fprintf(f, ", ");
logLit(f, ls[i]);
}
}
fprintf(f, "] ");
}
static inline const char* showBool(bool b) { return b ? "true" : "false"; }
// Just like 'assert()' but expression will be evaluated in the release version as well.
static inline void check(bool expr) { assert(expr); }
inline void Solver::printLit(Lit l)
{
reportf("%s%d:%c", sign(l) ? "-" : "", var(l)+1, value(l) == l_True ? '1' : (value(l) == l_False ? '0' : 'X'));
}
template<class C>
inline void Solver::printClause(const C& c)
{
for (int i = 0; i < c.size(); i++){
printLit(c[i]);
fprintf(stderr, " ");
}
}
//=================================================================================================
#endif