sat-solver/SatSolver.h

/****************************************************************************************[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,
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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
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**************************************************************************************************/

#ifndef Solver_h
#define Solver_h

#include <cstdio>
#include <string>

using namespace std;

#include "Vec.h"
#include "Heap.h"
#include "Alg.h"

#include "SolverTypes.h"


//=================================================================================================
// Solver -- the main class:

namespace minisat
{


class Solver {

        friend class SkeletonSolver;

public:

    // Constructor/Destructor:
    //
    Solver();
    ~Solver();



    // Problem specification:
    //
    Var     newVar    (bool polarity = true, bool dvar = true);
    // Add a new variable with parameters specifying variable mode.

    void reserveVars(int num_vars);

    bool    addClause (vec<Lit>& ps);
    // Add a clause to the solver. NOTE! 'ps' may be shrunk by this method!



    // 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;


    // 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                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();
    string clause_to_string(Clause& c);

    // 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