public static class GoodEqualsFactory {
    public static Object good(
        String a,
        int b,
        // oneConstantOnly doesn't matter since it's not nullable and can be only 1 value.
        @SuppressWarnings("unused") OneConstantEnum oneConstantOnly,
        // noConstant doesn't matter since it can only be null
        @SuppressWarnings("unused") @Nullable NoConstantEnum noConstant) {
      return new GoodEquals(a, b);
    }

   *
   * <p>Since Strings are immutable and built into the jdk we can optimize some operations
   *
   * <ul>
   *   <li>use {@link StringReader} instead of {@link CharSequenceReader}. It is faster since it can
   *       use {@link String#getChars(int, int, char[], int)} instead of copying characters one by
   *       one with {@link CharSequence#charAt(int)}.

   * element in the underlying collection and determine which elements satisfy the filter. When a
   * live view is <i>not</i> needed, it may be faster to copy {@code Iterables.filter(unfiltered,
   * predicate)} and use the copy.
   *
   * <p><b>Warning:</b> {@code predicate} must be <i>consistent with equals</i>, as documented at

   * under the assumption that for long-running instances, observed
   * contention levels will recur, so the cells will eventually be
   * needed again; and for short-lived ones, it does not matter.
   */

  /**
   * Padded variant of AtomicLong supporting only raw accesses plus CAS. The value field is placed
   * between pads, hoping that the JVM doesn't reorder them.
   *

   * query than the original; your mileage may vary. Precomputation takes time and is likely to be
   * worthwhile only if the precomputed matcher is queried many thousands of times.
   *
   * <p>This method has no effect (returns {@code this}) when called in GWT: it's unclear whether a
   * precomputed matcher is faster, but it certainly consumes more memory, which doesn't seem like a

        for (int i = 0; i < array.length; i++) {
          array[i] = counter.getAndIncrement();
        }
        builder.addAll(ImmutableLongArray.copyOf(array));
      }
    },
    ADD_LARGER_ARRAY {
      @Override
      void doIt(ImmutableLongArray.Builder builder, AtomicLong counter) {
        long[] array = new long[RANDOM.nextInt(200) + 200];
        for (int i = 0; i < array.length; i++) {

        for (int i = 0; i < array.length; i++) {
          array[i] = counter.getAndIncrement();
        }
        builder.addAll(ImmutableDoubleArray.copyOf(array));
      }
    },
    ADD_LARGER_ARRAY {
      @Override
      void doIt(ImmutableDoubleArray.Builder builder, AtomicInteger counter) {
        double[] array = new double[RANDOM.nextInt(200) + 200];
        for (int i = 0; i < array.length; i++) {

      // but work beyond that must take at least one second
      assertTrue(afterBurst >= 1000);
    }
  }

  /**
   * This neat test shows that no matter what weights we use in our requests, if we push X amount of
   * permits in a cool state, where X = rate * timeToCoolDown, and we have specified a
   * timeToWarmUp() period, it will cost as the prescribed amount of time. E.g., calling

  }

  int getSuccessor(int entryIndex) {
    return (entryIndex + 1 < size) ? entryIndex + 1 : -1;
  }

  /**
   * Updates the index an iterator is pointing to after a call to remove: returns the index of the
   * entry that should be looked at after a removal on indexRemoved, with indexBeforeRemove as the
   * index that *was* the next entry that would be looked at.
   */

     * the current count of the element in the multiset, depending on the implementation. Note that
     * in the former case, this method can never return zero, while in the latter, it will return
     * zero if all occurrences of the element were since removed from the multiset.
     *
     * @return the count of the element; never negative
     */
    int getCount();

    /**