/****************************************************************************************[Solver.h]
 Glucose -- Copyright (c) 2009, Gilles Audemard, Laurent Simon
                                CRIL - Univ. Artois, France
                                LRI  - Univ. Paris Sud, France

Glucose sources are based on MiniSat (see below MiniSat copyrights). Permissions
and copyrights of Glucose are exactly the same as Minisat on which it is based
on. (see below).

---------------
Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
Copyright (c) 2007-2010, 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 Glucose_Solver_h
#define Glucose_Solver_h

#include <fstream>
#include <iostream>

#include "core/BoundedQueue.h"
#include "core/Constants.h"
#include "core/SolverTypes.h"
#include "mtl/Alg.h"
#include "mtl/Heap.h"
#include "mtl/Vec.h"
#include "utils/Options.h"

namespace Glucose {

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

class Solver {
public:
  std::ostream *cert;

  // Constructor/Destructor:
  //
  Solver(std::ostream *certif = NULL);
  virtual ~Solver();

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

  bool addClause(const vec<Lit> &ps); // Add a clause to the solver.
  bool
  addEmptyClause(); // Add the empty clause, making the solver contradictory.
  bool addClause(Lit p);               // Add a unit clause to the solver.
  bool addClause(Lit p, Lit q);        // Add a binary clause to the solver.
  bool addClause(Lit p, Lit q, Lit r); // Add a ternary clause to the solver.
  bool addClause_(
      vec<Lit> &ps); // Add a clause to the solver without making superflous
                     // internal copy. Will change the passed vector '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.
  lbool solveLimited(
      const vec<Lit> &assumps); // Search for a model that respects a given set
                                // of assumptions (With resource constraints).
  bool solve();                 // Search without assumptions.
  bool solve(Lit p); // Search for a model that respects a single assumption.
  bool solve(Lit p, Lit q); // Search for a model that respects two assumptions.
  bool solve(Lit p, Lit q,
             Lit r); // Search for a model that respects three assumptions.
  bool okay() const; // FALSE means solver is in a conflicting state

  void toDimacs(FILE *f,
                const vec<Lit> &assumps); // Write CNF to file in DIMACS-format.
  void toDimacs(const char *file, const vec<Lit> &assumps);
  void toDimacs(FILE *f, Clause &c, vec<Var> &map, Var &max);
  void printLit(Lit l);
  void printClause(CRef c);
  void printInitialClause(CRef c);
  // Convenience versions of 'toDimacs()':
  void toDimacs(const char *file);
  void toDimacs(const char *file, Lit p);
  void toDimacs(const char *file, Lit p, Lit q);
  void toDimacs(const char *file, Lit p, Lit q, Lit r);

  // 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(Var x) const; // The value of a variable in the last model. The
                           // last call to solve must have been satisfiable.
  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.
  int nFreeVars() const;

  // Incremental mode
  void setIncrementalMode();
  void initNbInitialVars(int nb);
  void printIncrementalStats();

  // Resource contraints:
  //
  void setConfBudget(int64_t x);
  void setPropBudget(int64_t x);
  void budgetOff();
  void interrupt(); // Trigger a (potentially asynchronous) interruption of the
                    // solver.
  void clearInterrupt(); // Clear interrupt indicator flag.

  // Memory managment:
  //
  virtual void garbageCollect();
  void checkGarbage(double gf);
  void checkGarbage();

  // 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:
  //
  int verbosity;
  int verbEveryConflicts;
  int showModel;
  // Constants For restarts
  double K;
  double R;
  double sizeLBDQueue;
  double sizeTrailQueue;

  // Constants for reduce DB
  int firstReduceDB;
  int incReduceDB;
  int specialIncReduceDB;
  unsigned int lbLBDFrozenClause;

  // Constant for reducing clause
  int lbSizeMinimizingClause;
  unsigned int lbLBDMinimizingClause;

  double var_decay;
  double clause_decay;
  double random_var_freq;
  double random_seed;
  int ccmin_mode;   // Controls conflict clause minimization (0=none, 1=basic,
                    // 2=deep).
  int phase_saving; // Controls the level of phase saving (0=none, 1=limited,
                    // 2=full).
  bool rnd_pol;     // Use random polarities for branching heuristics.
  bool
      rnd_init_act; // Initialize variable activities with a small random value.
  double garbage_frac; // The fraction of wasted memory allowed before a garbage
                       // collection is triggered.

  // Certified UNSAT ( Thanks to Marijn Heule)
  FILE *certifiedOutput;
  bool certifiedUNSAT;

  // Statistics: (read-only member variable)
  //
  uint64_t nbRemovedClauses, nbReducedClauses, nbDL2, nbBin, nbUn, nbReduceDB,
      solves, starts, decisions, rnd_decisions, propagations, conflicts,
      conflictsRestarts, nbstopsrestarts, nbstopsrestartssame,
      lastblockatrestart;
  uint64_t dec_vars, clauses_literals, learnts_literals, max_literals,
      tot_literals;

public:
  long curRestart;
  // Helper structures:
  //
  struct VarData {
    CRef reason;
    int level;
  };
  static inline VarData mkVarData(CRef cr, int l) {
    VarData d = {cr, l};
    return d;
  }

  struct Watcher {
    CRef cref;
    Lit blocker;
    Watcher(CRef cr, Lit p) : cref(cr), blocker(p) {}
    bool operator==(const Watcher &w) const { return cref == w.cref; }
    bool operator!=(const Watcher &w) const { return cref != w.cref; }
  };

  struct WatcherDeleted {
    const ClauseAllocator &ca;
    WatcherDeleted(const ClauseAllocator &_ca) : ca(_ca) {}
    bool operator()(const Watcher &w) const { return ca[w.cref].mark() == 1; }
  };

  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) {}
  };

  // Solver state:
  //
  int lastIndexRed;
  bool ok; // If FALSE, the constraints are already unsatisfiable. No part of
           // the solver state may be used!
  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.
  OccLists<Lit, vec<Watcher>, WatcherDeleted>
      watches; // 'watches[lit]' is a list of constraints watching 'lit' (will
               // go there if literal becomes true).
  OccLists<Lit, vec<Watcher>, WatcherDeleted>
      watchesBin;    // 'watches[lit]' is a list of constraints watching 'lit'
                     // (will go there if literal becomes true).
  vec<CRef> clauses; // List of problem clauses.
  vec<CRef> learnts; // List of learnt clauses.

  vec<lbool> assigns; // The current assignments.
  vec<char> polarity; // The preferred polarity of each variable.
  vec<char> decision; // 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> nbpos;
  vec<int>
      trail_lim; // Separator indices for different decision levels in 'trail'.
  vec<VarData> vardata; // Stores reason and level for each variable.
  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 progress_estimate;    // Set by 'search()'.
  bool remove_satisfied; // Indicates whether possibly inefficient linear scan
                         // for satisfied clauses should be performed in
                         // 'simplify'.
  vec<unsigned int> permDiff; // permDiff[var] contains the current conflict
                              // number... Used to count the number of  LBD

#ifdef UPDATEVARACTIVITY
  // UPDATEVARACTIVITY trick (see competition'09 companion paper)
  vec<Lit> lastDecisionLevel;
#endif

  ClauseAllocator ca;

  int nbclausesbeforereduce; // To know when it is time to reduce clause
                             // database

  bqueue<unsigned int> trailQueue, lbdQueue; // Bounded queues for restarts.
  float sumLBD; // used to compute the global average of LBD. Restarts...
  int sumAssumptions;

  // 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;
  unsigned int MYFLAG;

  double max_learnts;
  double learntsize_adjust_confl;
  int learntsize_adjust_cnt;

  // Resource contraints:
  //
  int64_t conflict_budget;    // -1 means no budget.
  int64_t propagation_budget; // -1 means no budget.
  bool asynch_interrupt;

  // Variables added for incremental mode
  int incremental;          // Use incremental SAT Solver
  int nbVarsInitialFormula; // nb VAR in formula without assumptions
                            // (incremental SAT)
  double totalTime4Sat, totalTime4Unsat;
  int nbSatCalls, nbUnsatCalls;
  vec<int> assumptionPositions, initialPositions;

  // Main internal methods:
  //
  void insertVarOrder(
      Var x); // Insert a variable in the decision order priority queue.
  Lit pickBranchLit();     // Return the next decision variable.
  void newDecisionLevel(); // Begins a new decision level.
  void
  uncheckedEnqueue(Lit p,
                   CRef from = CRef_Undef); // Enqueue a literal. Assumes value
                                            // of literal is undefined.
  bool enqueue(Lit p,
               CRef from = CRef_Undef); // Test if fact 'p' contradicts current
                                        // state, enqueue otherwise.
  CRef
  propagate(); // Perform unit propagation. Returns possibly conflicting clause.
  void cancelUntil(int level); // Backtrack until a certain level.
  void analyze(CRef confl, vec<Lit> &out_learnt, vec<Lit> &selectors,
               int &out_btlevel, unsigned int &nblevels,
               unsigned int &szWithoutSelectors); // (bt = backtrack)
  void analyzeFinal(
      Lit p,
      vec<Lit> &out_conflict); // COULD THIS BE IMPLEMENTED BY THE ORDINARIY
                               // "analyze" BY SOME REASONABLE GENERALIZATION?
  bool
  // (helper method for 'analyze()')
  litRedundant(Lit p, uint32_t abstract_levels);

  // Search for a given number of conflicts.
  lbool search(int nof_conflicts);

  // Main solve method (assumptions given in 'assumptions').
  lbool solve_(bool rebuildHeap = true, int nbConflict = 0);

  // Reduce the set of learnt clauses.
  void reduceDB();

  // Shrink 'cs' to contain only non-satisfied clauses.
  void removeSatisfied(vec<CRef> &cs);

  void rebuildOrderHeap();

  // Maintaining Variable/Clause activity:
  //
  void
  varDecayActivity(); // Decay all variables with the specified factor.
                      // Implemented by increasing the 'bump' value instead.
  void varBumpActivity(
      Var v, double inc); // Increase a variable with the current 'bump' value.
  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(CRef cr); // Attach a clause to watcher lists.
  void detachClause(CRef cr,
                    bool strict = false); // Detach a clause to watcher lists.
  void removeClause(CRef cr);             // 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.

  unsigned int computeLBD(const vec<Lit> &lits, int end = -1);
  unsigned int computeLBD(const Clause &c);
  void minimisationWithBinaryResolution(vec<Lit> &out_learnt);

  void relocAll(ClauseAllocator &to);

  // Misc:
  //
  int decisionLevel() const; // Gives the current decisionlevel.
  uint32_t abstractLevel(Var x)
      const; // Used to represent an abstraction of sets of decision levels.
  CRef reason(Var x) const;
  int level(Var x) const;
  double progressEstimate() const; // DELETE THIS ?? IT'S NOT VERY USEFUL ...
  bool withinBudget() const;
  inline bool isSelector(Var v) {
    return (incremental && v > nbVarsInitialFormula);
  }

  // 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);
  }

  // added to be linked with d4.
  bool reversePolarity = false;
  vec<double> scoreActivity;
  vec<Var> problemVariable;
  vec<Var> vsRebuildOrderHeap;
  vec<int> inTheHeap;
  int stampInTheHeap;
  inline bool isInTheHeap(Var v) { return inTheHeap[v] == stampInTheHeap; }

  inline void rebuildWithConnectedComponent(vec<Var> &v) {
    v.copyTo(problemVariable);
    stampInTheHeap++;
    for (int j = 0; j < v.size(); j++)
      if (value(v[j]) == l_Undef)
        inTheHeap[v[j]] = stampInTheHeap;
    rebuildOrderHeap();
  } // rebuidWithConnectedComponent

  inline void rebuildWithAllVar() {
    problemVariable.setSize(0);
    stampInTheHeap++;
    for (Var v = 0; v < nVars(); v++) {
      if (value(v) != l_Undef)
        continue;
      inTheHeap[v] = stampInTheHeap;
      problemVariable.push(v);
    }
    rebuildOrderHeap();
  } // rebuildWithAllVar

  inline bool solveWithAssumptions() {
    budgetOff();
    bool ret = solve_(false) == l_True;
    return ret;
  } // solveWithAssumptions

  /**
   * @brief Propagate the assumption.
   *
   * @return true if no conflict, false otherwise.
   */
  inline bool propagateAssumption();

  inline bool isUndef(Lit l) { return value(l) == l_Undef; }
  inline bool isSAT(Lit l) { return value(l) == l_True; }

  inline void showTrail() {
    printf("--> %d: ", decisionLevel());
    for (int i = 0; i < trail.size(); i++) {
      printf("%d(%d) ", readableLit(trail[i]), level(var(trail[i])));
    }
    printf("\n");
  }

  inline bool isAssigned(Var v) { return value(v) != l_Undef; }
  inline Lit litAssigned(Var v) {
    if (value(v) == l_Undef)
      return lit_Undef;
    return mkLit(v, value(v) == l_False);
  }

  void analyzeLastUIP(CRef confl, vec<Lit> &out_learnt,
                      int &out_btlevel); // (bt = backtrack)

  bool needModel = false;
  inline void setNeedModel(bool b) { needModel = b; }
  int idxClausesCpt = 0;

  inline bool litTrueInLastModel(Lit l) { return modelValue(l) == l_True; }

  /**

   * @brief Insert a clause and check if we have to propagate something.
   *
   */
  inline void insertClauseAndPropagate(vec<Lit> &cl) {
    // printf("clause: "); showListLit(cl);
    if (cert != nullptr) {
      std::ostream &cval = *cert;
      for (int i = 0; i < cl.size(); i++)
        cval << (var(cl[i]) + 1) * (-2 * sign(cl[i]) + 1) << " ";
      cval << "0\n";
    }

    idxClausesCpt++;
    if (cl.size() > 1) {
      int posHigherLevel = 1;
      for (int j = 2; j < cl.size(); j++)
        if (level(var(cl[j])) > level(var(cl[posHigherLevel])))
          posHigherLevel = j;
      Lit tmp = cl[posHigherLevel];
      cl[posHigherLevel] = cl[1];
      cl[1] = tmp;

      cancelUntil(level(var(cl[1])));
      CRef cr = ca.alloc(cl, true);
      learnts.push(cr);
      attachClause(cr);
      uncheckedEnqueue(cl[0], cr);
      ca[cr].idxReason(idxClausesCpt);
    } else {
      cancelUntil(0);
      uncheckedEnqueue(cl[0]);
    }

    propagate();

    while (decisionLevel() < assumptions.size()) {
      Lit p = assumptions[decisionLevel()];
      newDecisionLevel();
      if (value(p) == l_Undef)
        uncheckedEnqueue(p);
      propagate();
    }
  } // insertClauseAndPropagate
};

//=================================================================================================
// Implementation of inline methods:

inline CRef Solver::reason(Var x) const { return vardata[x].reason; }
inline int Solver::level(Var x) const { return vardata[x].level; }

inline void Solver::insertVarOrder(Var x) {
  if (!order_heap.inHeap(x) && decision[x])
    order_heap.insert(x);
}

inline void Solver::varDecayActivity() { var_inc *= (1 / var_decay); }
inline void Solver::varBumpActivity(Var v) { varBumpActivity(v, var_inc); }
inline void Solver::varBumpActivity(Var v, double inc) {
  scoreActivity[v] += 1;
  if ((activity[v] += 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 *= (1 / clause_decay); }
inline void Solver::claBumpActivity(Clause &c) {
  if ((c.activity() += cla_inc) > 1e20) {
    // Rescale:
    for (int i = 0; i < learnts.size(); i++)
      ca[learnts[i]].activity() *= 1e-20;
    cla_inc *= 1e-20;
  }
}

inline void Solver::checkGarbage(void) { return checkGarbage(garbage_frac); }
inline void Solver::checkGarbage(double gf) {
  if (ca.wasted() > ca.size() * gf)
    garbageCollect();
}

// NOTE: enqueue does not set the ok flag! (only public methods do)
inline bool Solver::enqueue(Lit p, CRef from) {
  return value(p) != l_Undef ? value(p) != l_False
                             : (uncheckedEnqueue(p, from), true);
}
inline bool Solver::addClause(const vec<Lit> &ps) {
  ps.copyTo(add_tmp);
  return addClause_(add_tmp);
}
inline bool Solver::addEmptyClause() {
  add_tmp.clear();
  return addClause_(add_tmp);
}
inline bool Solver::addClause(Lit p) {
  add_tmp.clear();
  add_tmp.push(p);
  return addClause_(add_tmp);
}
inline bool Solver::addClause(Lit p, Lit q) {
  add_tmp.clear();
  add_tmp.push(p);
  add_tmp.push(q);
  return addClause_(add_tmp);
}
inline bool Solver::addClause(Lit p, Lit q, Lit r) {
  add_tmp.clear();
  add_tmp.push(p);
  add_tmp.push(q);
  add_tmp.push(r);
  return addClause_(add_tmp);
}
inline bool Solver::locked(const Clause &c) const {
  if (c.size() > 2)
    return value(c[0]) == l_True && reason(var(c[0])) != CRef_Undef &&
           ca.lea(reason(var(c[0]))) == &c;
  return (value(c[0]) == l_True && reason(var(c[0])) != CRef_Undef &&
          ca.lea(reason(var(c[0]))) == &c) ||
         (value(c[1]) == l_True && reason(var(c[1])) != CRef_Undef &&
          ca.lea(reason(var(c[1]))) == &c);
}
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 assigns[x]; }
inline lbool Solver::value(Lit p) const { return assigns[var(p)] ^ sign(p); }
inline lbool Solver::modelValue(Var x) const { return model[x]; }
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 vardata.size(); }
inline int Solver::nFreeVars() const {
  return (int)dec_vars - (trail_lim.size() == 0 ? trail.size() : trail_lim[0]);
}
inline void Solver::setPolarity(Var v, bool b) { polarity[v] = b; }
inline void Solver::setDecisionVar(Var v, bool b) {
  if (b && !decision[v])
    dec_vars++;
  else if (!b && decision[v])
    dec_vars--;

  decision[v] = b;
  insertVarOrder(v);
}
inline void Solver::setConfBudget(int64_t x) {
  conflict_budget = conflicts + x;
}
inline void Solver::setPropBudget(int64_t x) {
  propagation_budget = propagations + x;
}
inline void Solver::interrupt() { asynch_interrupt = true; }
inline void Solver::clearInterrupt() { asynch_interrupt = false; }
inline void Solver::budgetOff() { conflict_budget = propagation_budget = -1; }
inline bool Solver::withinBudget() const {
  return !asynch_interrupt &&
         (conflict_budget < 0 || conflicts < (uint64_t)conflict_budget) &&
         (propagation_budget < 0 ||
          propagations < (uint64_t)propagation_budget);
}

// FIXME: after the introduction of asynchronous interrruptions the
// solve-versions that return a pure bool do not give a safe interface. Either
// interrupts must be possible to turn off here, or all calls to solve must
// return an 'lbool'. I'm not yet sure which I prefer.
inline bool Solver::solve() {
  budgetOff();
  assumptions.clear();
  return solve_() == l_True;
}
inline bool Solver::solve(Lit p) {
  budgetOff();
  assumptions.clear();
  assumptions.push(p);
  return solve_() == l_True;
}
inline bool Solver::solve(Lit p, Lit q) {
  budgetOff();
  assumptions.clear();
  assumptions.push(p);
  assumptions.push(q);
  return solve_() == l_True;
}
inline bool Solver::solve(Lit p, Lit q, Lit r) {
  budgetOff();
  assumptions.clear();
  assumptions.push(p);
  assumptions.push(q);
  assumptions.push(r);
  return solve_() == l_True;
}
inline bool Solver::solve(const vec<Lit> &assumps) {
  budgetOff();
  assumps.copyTo(assumptions);
  return solve_() == l_True;
}
inline lbool Solver::solveLimited(const vec<Lit> &assumps) {
  assumps.copyTo(assumptions);
  return solve_();
}
inline bool Solver::okay() const { return ok; }

inline void Solver::toDimacs(const char *file) {
  vec<Lit> as;
  toDimacs(file, as);
}
inline void Solver::toDimacs(const char *file, Lit p) {
  vec<Lit> as;
  as.push(p);
  toDimacs(file, as);
}
inline void Solver::toDimacs(const char *file, Lit p, Lit q) {
  vec<Lit> as;
  as.push(p);
  as.push(q);
  toDimacs(file, as);
}
inline void Solver::toDimacs(const char *file, Lit p, Lit q, Lit r) {
  vec<Lit> as;
  as.push(p);
  as.push(q);
  as.push(r);
  toDimacs(file, as);
}

//=================================================================================================
// Debug etc:

inline void Solver::printLit(Lit l) {
  printf("%s%d:%c", sign(l) ? "-" : "", var(l) + 1,
         value(l) == l_True ? '1' : (value(l) == l_False ? '0' : 'X'));
}

inline void Solver::printClause(CRef cr) {
  Clause &c = ca[cr];
  for (int i = 0; i < c.size(); i++) {
    printLit(c[i]);
    printf(" ");
  }
}

inline void Solver::printInitialClause(CRef cr) {
  Clause &c = ca[cr];
  for (int i = 0; i < c.size(); i++) {
    if (!isSelector(var(c[i]))) {
      printLit(c[i]);
      printf(" ");
    }
  }
}

//=================================================================================================
} // namespace Glucose

#endif