{
              int delta = random.nextInt(6); // [0, 5]
              int oldValue = multiset.remove(key, delta);
              deltas[keyIndex] -= Math.min(delta, oldValue);
              break;
            }
          case REMOVE_EXACTLY:
            {
              int delta = random.nextInt(5); // [0, 4]
              if (multiset.removeExactly(key, delta)) {
                deltas[keyIndex] -= delta;

  private int value;

  Count(int value) {
    this.value = value;
  }

  public int get() {
    return value;
  }

  public void add(int delta) {
    value += delta;
  }

  public int addAndGet(int delta) {
    return value += delta;
  }

  public void set(int newValue) {
    value = newValue;
  }

  public int getAndSet(int newValue) {
    int result = value;
    value = newValue;

  }

  /**
   * Adds {@code delta} to the value currently associated with {@code key}, and returns the new
   * value.
   */
  @CanIgnoreReturnValue
  public long addAndGet(K key, long delta) {
    outer:
    while (true) {
      AtomicLong atomic = map.get(key);
      if (atomic == null) {
        atomic = map.putIfAbsent(key, new AtomicLong(delta));
        if (atomic == null) {

   *
   * @param i the index
   * @param delta the value to add
   * @return the previous value
   */
  @CanIgnoreReturnValue
  public final double getAndAdd(int i, double delta) {
    while (true) {
      long current = longs.get(i);
      double currentVal = longBitsToDouble(current);
      double nextVal = currentVal + delta;
      long next = doubleToRawLongBits(nextVal);

        while (!diff) {
          int delta = (1 << i) | (1 << j);
          int key1 = rand.nextInt();
          // apply delta
          int key2 = key1 ^ delta;

          // get hashes
          int hash1 = function.hashInt(key1).asInt();
          int hash2 = function.hashInt(key2).asInt();

          // this 2-bit candidate delta is not a characteristic
          // if deltas are different

        double mean = meanAlgorithm.mean(values);
        double sumOfSquaresOfDeltas = 0.0;
        for (double value : values) {
          double delta = value - mean;
          sumOfSquaresOfDeltas += delta * delta;
        }
        return new MeanAndVariance(mean, sumOfSquaresOfDeltas / values.length);
      }
    },
    KAHAN {
      @Override

  }

  private static Function<Integer, Integer> add(final int delta) {
    return new Function<Integer, Integer>() {
      @Override
      public Integer apply(Integer input) {
        return input + delta;
      }
    };
  }

  private static AsyncCallable<Integer> asyncAdd(
      final ListenableFuture<Integer> future, final int delta, final Executor executor) {
    return new AsyncCallable<Integer>() {

  }

  private static Function<Integer, Integer> add(final int delta) {
    return new Function<Integer, Integer>() {
      @Override
      public Integer apply(Integer input) {
        return input + delta;
      }
    };
  }

  private static AsyncCallable<Integer> asyncAdd(
      final ListenableFuture<Integer> future, final int delta, final Executor executor) {
    return new AsyncCallable<Integer>() {

            Long.MIN_VALUE,
            Long.MAX_VALUE)) {
      for (double delta : Doubles.asList(0.0, 1.0, 2.0)) {
        integralBuilder.addAll(Doubles.asList(d + delta, d - delta, -d - delta, -d + delta));
      }
      for (double delta : Doubles.asList(0.01, 0.1, 0.25, 0.499, 0.5, 0.501, 0.7, 0.8)) {
        double x = d + delta;
        if (x != Math.round(x)) {
          fractionalBuilder.add(x);
        }
      }

      // This range is [-5, 4] - slight negative bias so we often hit zero, which brings the
      // auto-removal of zeroes into play.
      int delta = random.nextInt(10) - 5;
      blah += delta;
      if (delta >= 0) {
        multiset.add(key, delta);
      } else {
        multiset.remove(key, -delta);
      }
    }
    return blah;
  }

  private enum MultisetSupplier {
    CONCURRENT_HASH_MULTISET() {