Package kodkod.engine.ucore

Source Code of kodkod.engine.ucore.RCEStrategy

/*
* Kodkod -- Copyright (c) 2005-2008, Emina Torlak
*
* 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.
*/
package kodkod.engine.ucore;

import kodkod.engine.fol2sat.TranslationLog;
import kodkod.engine.fol2sat.Translator;
import kodkod.engine.satlab.ReductionStrategy;
import kodkod.engine.satlab.ResolutionTrace;
import kodkod.util.ints.IntCollection;
import kodkod.util.ints.IntIterator;
import kodkod.util.ints.IntSet;
import kodkod.util.ints.Ints;

/**
* Recycling Core Extraction is a strategy for generating unsat cores that are minimal at the logic level. 
* Specifically, let C be a core that is minimal according to this strategy,
* and let F(C) be the top-level logic constraints
* corresponding to C.  Then, this strategy guarantees that there is no clause
* c in C such that F(C - c) is a strict subset of F(C). Furthermore, it also
* guarantees that for all f in F(C), F(C) - f is satisfiable.  This is a stronger
* guarantee than that of {@linkplain HybridStrategy}.  In general, using this strategy
* is more expensive, timewise, than using {@linkplain HybridStrategy}.
*
* <p>This implementation of RCE will work properly only on CNFs generated by the kodkod {@linkplain Translator}. </p>
* @author Emina Torlak
* @see HybridStrategy
*/
public class RCEStrategy implements ReductionStrategy {
  private final IntCollection varsToTry;
  private final int dist;
 
  /**
   * Constructs an RCE strategy that will use the given translation
   * log to relate the cnf clauses back to the logic constraints from
   * which they were generated. By default, all relevant resolvents
   * are used in each iteration.
   */
  public RCEStrategy(final TranslationLog log) {
    this(log, Integer.MAX_VALUE);
  }
 

  /**
   * Constructs an RCE strategy that will use the given translation
   * log to relate the cnf clauses back to the logic constraints from
   * which they were generated. The relevant resolvents
   * used in each iteration are reachable from the relevant axioms
   * in at most <tt>dist</tt> steps.
   * @requires dist >= 0
   */
  public RCEStrategy(final TranslationLog log, int dist) {
    if (dist<0) throw new IllegalArgumentException("Resolution distance must be non-negative: " + dist);
    varsToTry = StrategyUtils.rootVars(log);
    this.dist = dist;
  }
 
 
  /**
   * {@inheritDoc}
   * @see kodkod.engine.satlab.ReductionStrategy#next(kodkod.engine.satlab.ResolutionTrace)
   */
  public IntSet next(ResolutionTrace trace) {
    if (varsToTry.isEmpty()) return Ints.EMPTY_SET; // tried everything
    final IntSet relevantVars = StrategyUtils.coreTailUnits(trace);
   
    for(IntIterator varItr = varsToTry.iterator(); varItr.hasNext();) {
      final int var = varItr.next();
      varItr.remove();
      if (relevantVars.remove(var)) { // remove maxVar from the set of relevant variables
        if (relevantVars.isEmpty()) break; // there was only root formula left
        // get all axioms and resolvents corresponding to the clauses that
        // form the translations of formulas identified by relevant vars
        final IntSet relevantClauses = clausesFor(trace, relevantVars);
        assert !relevantClauses.isEmpty() && !relevantClauses.contains(trace.size()-1);
        return relevantClauses;
      }
    }
   
    varsToTry.clear();   
    return Ints.EMPTY_SET;
  }
 

  /**
   * Returns the indices of all axioms and resolvents
   * in the given trace that form the translations of the formulas
   * identified by the given variables.  This method assumes that
   * the axioms in the given trace were generated by the Kodkod
   * {@linkplain Translator}.
   * @return
   * let C = { c: trace.prover.clauses | c.maxVariable() in relevantVars },
   *     T = { c1, c2: C | c2.maxVariable() in abs(c1.literals) },
   *     A = C.*T |
   *     trace.backwardReachable(A) - trace.backwardReachable(trace.axioms() - A)
   */
  private IntSet clausesFor(ResolutionTrace trace, IntSet relevantVars) {

    final IntSet relevantAxioms = StrategyUtils.clausesFor(trace, relevantVars);

    if (dist<trace.resolvents().size()) {
      IntSet relevant = relevantAxioms;
      for(int i = 0, lastSize = 0; lastSize < relevant.size() && i < dist; i++) {
        lastSize = relevant.size();
        relevant = trace.directlyLearnable(relevant);
      }
      return relevant;
    } else {
      return trace.learnable(relevantAxioms); // return all resolvents
    }
   
 
//    System.out.println("level 1 resolvents " + (relevant.size()-relevantAxioms.size()) + ",  axioms " + relevantAxioms.size());
   
  }
}
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