}

  /** CASes the busy field from 0 to 1 to acquire lock. */
  final boolean casBusy() {
    return UNSAFE.compareAndSwapInt(this, BUSY_OFFSET, 0, 1);
  }

  /**
   * Computes the function of current and new value. Subclasses should open-code this update
   * function for most uses, but the virtualized form is needed within retryUpdate.
   *

        if (pageSize > 0) {
            calculatePageInfo();
        }
    }

    /**
     * Calculates pagination information based on the current parameters.
     * This method computes page counts, navigation flags, record numbers, and page number lists.
     */
    protected void calculatePageInfo() {
        int startWithOffset = start - offset;
        if (startWithOffset < 0) {

  public ImmutableCollection<V> values() {
    if (cachedValues != null) {
      return cachedValues;
    }
    return cachedValues = createValues();
  }

  // cached so that this.multimapView().inverse() only computes inverse once
  private transient @Nullable ImmutableSetMultimap<K, V> multimapView;

  public ImmutableSetMultimap<K, V> asMultimap() {
    ImmutableSetMultimap<K, V> result = multimapView;
    return (result == null)

      put(range, value);
      return;
    }

    Range<K> coalescedRange = coalescedRange(range, checkNotNull(value));
    put(coalescedRange, value);
  }

  /** Computes the coalesced range for the given range+value - does not mutate the map. */
  private Range<K> coalescedRange(Range<K> range, V value) {
    Range<K> coalescedRange = range;
    Entry<Cut<K>, RangeMapEntry<K, V>> lowerEntry =

   * computes) correspond to minimum intervals between subsequent requests, for the specified number
   * of requested permits.
   *
   * Here is an example of storedPermitsToWaitTime: If storedPermits == 10.0, and we want 3 permits,
   * we take them from storedPermits, reducing them to 7.0, and compute the throttling for these as

    assertEquals(expectedMean, IntMath.mean(x, y));
    assertEquals(
        "The mean of x and y should equal the mean of y and x", expectedMean, IntMath.mean(y, x));
  }

  /**
   * Computes the mean in a way that is obvious and resilient to overflow by using BigInteger
   * arithmetic.
   */
  private static int computeMeanSafely(int x, int y) {
    BigInteger bigX = BigInteger.valueOf(x);

    assertEquals(expectedMean, IntMath.mean(x, y));
    assertEquals(
        "The mean of x and y should equal the mean of y and x", expectedMean, IntMath.mean(y, x));
  }

  /**
   * Computes the mean in a way that is obvious and resilient to overflow by using BigInteger
   * arithmetic.
   */
  private static int computeMeanSafely(int x, int y) {
    BigInteger bigX = BigInteger.valueOf(x);

        // This work was already done by calling lruEntries.get().
      }

      else -> {
        throw IOException("unexpected journal line: $line")
      }
    }
  }

  /**
   * Computes the initial size and collects garbage as a part of opening the cache. Dirty entries
   * are assumed to be inconsistent and will be deleted.
   */
  @Throws(IOException::class)
  private fun processJournal() {

    assertEquals(expectedMean, LongMath.mean(x, y));
    assertEquals(
        "The mean of x and y should equal the mean of y and x", expectedMean, LongMath.mean(y, x));
  }

  /**
   * Computes the mean in a way that is obvious and resilient to overflow by using BigInteger
   * arithmetic.
   */
  private static long computeMeanSafely(long x, long y) {
    BigInteger bigX = BigInteger.valueOf(x);

    default Map<String, String> getEffectiveProperties() {
        return getEffectiveProperties(null);
    }

    /**
     * Each invocation computes a new map of effective properties. To be used in interpolation.
     * <p>
     * Effective properties are computed from system, user and optionally project properties, layered with
     * defined precedence onto each other to achieve proper precedence. Precedence is defined as: