Program: 57328
Project: 57328
Buggy source:
/** 
 * {@inheritDoc} 
 */
@Override public double integrate(final FirstOrderDifferentialEquations equations,final double t0,final double[] y0,final double t,final double[] y) throws MathUserException, IntegratorException {
  sanityChecks(equations,t0,y0,t,y);
  setEquations(equations);
  resetEvaluations();
  final boolean forward=t > t0;
  final int stages=c.length + 1;
  if (y != y0) {
    System.arraycopy(y0,0,y,0,y0.length);
  }
  final double[][] yDotK=new double[stages][y0.length];
  final double[] yTmp=new double[y0.length];
  final double[] yDotTmp=new double[y0.length];
  AbstractStepInterpolator interpolator;
  if (requiresDenseOutput()) {
    final RungeKuttaStepInterpolator rki=(RungeKuttaStepInterpolator)prototype.copy();
    rki.reinitialize(this,yTmp,yDotK,forward);
    interpolator=rki;
  }
 else {
    interpolator=new DummyStepInterpolator(yTmp,yDotK[stages - 1],forward);
  }
  interpolator.storeTime(t0);
  stepStart=t0;
  double hNew=0;
  boolean firstTime=true;
  for (  StepHandler handler : stepHandlers) {
    handler.reset();
  }
  statesInitialized=false;
  isLastStep=false;
  do {
    interpolator.shift();
    double error=10;
    while (error >= 1.0) {
      if (firstTime || !fsal) {
        computeDerivatives(stepStart,y,yDotK[0]);
      }
      if (firstTime) {
        final double[] scale=new double[mainSetDimension];
        if (vecAbsoluteTolerance == null) {
          for (int i=0; i < scale.length; ++i) {
            scale[i]=scalAbsoluteTolerance + scalRelativeTolerance * FastMath.abs(y[i]);
          }
        }
 else {
          for (int i=0; i < scale.length; ++i) {
            scale[i]=vecAbsoluteTolerance[i] + vecRelativeTolerance[i] * FastMath.abs(y[i]);
          }
        }
        hNew=initializeStep(equations,forward,getOrder(),scale,stepStart,y,yDotK[0],yTmp,yDotK[1]);
        firstTime=false;
      }
      stepSize=hNew;
      for (int k=1; k < stages; ++k) {
        for (int j=0; j < y0.length; ++j) {
          double sum=a[k - 1][0] * yDotK[0][j];
          for (int l=1; l < k; ++l) {
            sum+=a[k - 1][l] * yDotK[l][j];
          }
          yTmp[j]=y[j] + stepSize * sum;
        }
        computeDerivatives(stepStart + c[k - 1] * stepSize,yTmp,yDotK[k]);
      }
      for (int j=0; j < y0.length; ++j) {
        double sum=b[0] * yDotK[0][j];
        for (int l=1; l < stages; ++l) {
          sum+=b[l] * yDotK[l][j];
        }
        yTmp[j]=y[j] + stepSize * sum;
      }
      error=estimateError(yDotK,y,yTmp,stepSize);
      if (error >= 1.0) {
        final double factor=FastMath.min(maxGrowth,FastMath.max(minReduction,safety * FastMath.pow(error,exp)));
        hNew=filterStep(stepSize * factor,forward,false);
      }
    }
    interpolator.storeTime(stepStart + stepSize);
    System.arraycopy(yTmp,0,y,0,y0.length);
    System.arraycopy(yDotK[stages - 1],0,yDotTmp,0,y0.length);
    stepStart=acceptStep(interpolator,y,yDotTmp,t);
    if (!isLastStep) {
      interpolator.storeTime(stepStart);
      if (fsal) {
        System.arraycopy(yDotTmp,0,yDotK[0],0,y0.length);
      }
      final double factor=FastMath.min(maxGrowth,FastMath.max(minReduction,safety * FastMath.pow(error,exp)));
      final double scaledH=stepSize * factor;
      final double nextT=stepStart + scaledH;
      final boolean nextIsLast=forward ? (nextT >= t) : (nextT <= t);
      hNew=filterStep(scaledH,forward,nextIsLast);
      final double filteredNextT=stepStart + hNew;
      final boolean filteredNextIsLast=forward ? (filteredNextT >= t) : (filteredNextT <= t);
      if (filteredNextIsLast) {
        hNew=t - stepStart;
      }
    }
  }
 while (!isLastStep);
  final double stopTime=stepStart;
  resetInternalState();
  return stopTime;
}

Fixed version (ground truth):
/** 
 * {@inheritDoc} 
 */
@Override public double integrate(final FirstOrderDifferentialEquations equations,final double t0,final double[] y0,final double t,final double[] y) throws MathUserException, IntegratorException {
  sanityChecks(equations,t0,y0,t,y);
  setEquations(equations);
  resetEvaluations();
  final boolean forward=t > t0;
  final int stages=c.length + 1;
  if (y != y0) {
    System.arraycopy(y0,0,y,0,y0.length);
  }
  final double[][] yDotK=new double[stages][y0.length];
  final double[] yTmp=new double[y0.length];
  final double[] yDotTmp=new double[y0.length];
  AbstractStepInterpolator interpolator;
  if (requiresDenseOutput()) {
    final RungeKuttaStepInterpolator rki=(RungeKuttaStepInterpolator)prototype.copy();
    rki.reinitialize(this,yTmp,yDotK,forward);
    interpolator=rki;
  }
 else {
    interpolator=new DummyStepInterpolator(yTmp,yDotK[stages - 1],forward);
  }
  interpolator.storeTime(t0);
  stepStart=t0;
  double hNew=0;
  boolean firstTime=true;
  for (  StepHandler handler : stepHandlers) {
    handler.reset();
  }
  setStateInitialized(false);
  isLastStep=false;
  do {
    interpolator.shift();
    double error=10;
    while (error >= 1.0) {
      if (firstTime || !fsal) {
        computeDerivatives(stepStart,y,yDotK[0]);
      }
      if (firstTime) {
        final double[] scale=new double[mainSetDimension];
        if (vecAbsoluteTolerance == null) {
          for (int i=0; i < scale.length; ++i) {
            scale[i]=scalAbsoluteTolerance + scalRelativeTolerance * FastMath.abs(y[i]);
          }
        }
 else {
          for (int i=0; i < scale.length; ++i) {
            scale[i]=vecAbsoluteTolerance[i] + vecRelativeTolerance[i] * FastMath.abs(y[i]);
          }
        }
        hNew=initializeStep(equations,forward,getOrder(),scale,stepStart,y,yDotK[0],yTmp,yDotK[1]);
        firstTime=false;
      }
      stepSize=hNew;
      for (int k=1; k < stages; ++k) {
        for (int j=0; j < y0.length; ++j) {
          double sum=a[k - 1][0] * yDotK[0][j];
          for (int l=1; l < k; ++l) {
            sum+=a[k - 1][l] * yDotK[l][j];
          }
          yTmp[j]=y[j] + stepSize * sum;
        }
        computeDerivatives(stepStart + c[k - 1] * stepSize,yTmp,yDotK[k]);
      }
      for (int j=0; j < y0.length; ++j) {
        double sum=b[0] * yDotK[0][j];
        for (int l=1; l < stages; ++l) {
          sum+=b[l] * yDotK[l][j];
        }
        yTmp[j]=y[j] + stepSize * sum;
      }
      error=estimateError(yDotK,y,yTmp,stepSize);
      if (error >= 1.0) {
        final double factor=FastMath.min(maxGrowth,FastMath.max(minReduction,safety * FastMath.pow(error,exp)));
        hNew=filterStep(stepSize * factor,forward,false);
      }
    }
    interpolator.storeTime(stepStart + stepSize);
    System.arraycopy(yTmp,0,y,0,y0.length);
    System.arraycopy(yDotK[stages - 1],0,yDotTmp,0,y0.length);
    stepStart=acceptStep(interpolator,y,yDotTmp,t);
    if (!isLastStep) {
      interpolator.storeTime(stepStart);
      if (fsal) {
        System.arraycopy(yDotTmp,0,yDotK[0],0,y0.length);
      }
      final double factor=FastMath.min(maxGrowth,FastMath.max(minReduction,safety * FastMath.pow(error,exp)));
      final double scaledH=stepSize * factor;
      final double nextT=stepStart + scaledH;
      final boolean nextIsLast=forward ? (nextT >= t) : (nextT <= t);
      hNew=filterStep(scaledH,forward,nextIsLast);
      final double filteredNextT=stepStart + hNew;
      final boolean filteredNextIsLast=forward ? (filteredNextT >= t) : (filteredNextT <= t);
      if (filteredNextIsLast) {
        hNew=t - stepStart;
      }
    }
  }
 while (!isLastStep);
  final double stopTime=stepStart;
  resetInternalState();
  return stopTime;
}