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