if (contentType != null) {
        sink
          .writeUtf8("Content-Type: ")
          .writeUtf8(contentType.toString())
          .write(CRLF)
      }

      // We can't measure the body's size without the sizes of its components.
      val contentLength = body.contentLength()
      if (contentLength == -1L && countBytes) {
        byteCountBuffer!!.clear()
        return -1L
      }

   * @param offset the offset into the array at which to start
   * @return the value found in the array in the form of a long
   */
  static int load32(byte[] source, int offset) {
    // TODO(user): Measure the benefit of delegating this to LittleEndianBytes also.
    return (source[offset] & 0xFF)
        | ((source[offset + 1] & 0xFF) << 8)
        | ((source[offset + 2] & 0xFF) << 16)

    }

    public void test_integrationScenarios() {
        // Test realistic scenarios combining multiple methods
        String memoryLog1 = MemoryUtil.getMemoryUsageLog();

        // Create some objects and measure their sizes
        List<String> testData = new ArrayList<>();
        for (int i = 0; i < 100; i++) {
            testData.add("test data " + i);
        }

        long listSize = MemoryUtil.sizeOf(testData);

          if ((hash1 & (1 << k)) == (hash2 & (1 << k))) {
            same[k] += 1;
          } else {
            diff[k] += 1;
          }
        }
      }
      // measure probability and assert it's within margin of error
      for (int j = 0; j < hashBits; j++) {
        double prob = (double) diff[j] / (double) (diff[j] + same[j]);
        assertThat(prob).isWithin(epsilon).of(0.50d);

 * may cause corruption or runtime errors if not. It may however be shared amongst multiple OkHttpClient
 * instances.
 *
 * ## Cache Optimization
 *
 * To measure cache effectiveness, this class tracks three statistics:
 *
 *  * **[Request Count:][requestCount]** the number of HTTP requests issued since this cache was
 *    created.

  public B withFeatures(Iterable<? extends Feature<?>> features) {
    for (Feature<?> feature : features) {
      this.features.add(feature);
    }
    return self();
  }

  public Set<Feature<?>> getFeatures() {
    return unmodifiableSet(features);
  }

  // Name

  private @Nullable String name;

  /** Configures this builder produce a TestSuite with the given name. */

evicts pods from nodes in preparation for disruptive operations like kernel
upgrades or maintenance.
     * Custom Metrics for Autoscaling (HorizontalPodAutoscaler API in the Autoscaling
API group): The Horizontal Pod Autoscaling feature now supports custom metrics
(Alpha), allowing you to specify application-level metrics and thresholds to
trigger scaling up and down the number of pods in your application.

   * @return the implied set of features
   */
  public static Set<Feature<?>> impliedFeatures(Set<Feature<?>> features) {
    Set<Feature<?>> impliedSet = new LinkedHashSet<>();
    Queue<Feature<?>> queue = new ArrayDeque<>(features);
    while (!queue.isEmpty()) {
      Feature<?> feature = queue.remove();
      for (Feature<?> implied : feature.getImpliedFeatures()) {
        if (!features.contains(implied) && impliedSet.add(implied)) {

      Set<Feature<?>> multimapFeatures) {
    Set<Feature<?>> derivedFeatures = copyToSet(multimapFeatures);
    derivedFeatures.remove(CollectionFeature.SERIALIZABLE);
    derivedFeatures.remove(CollectionFeature.SERIALIZABLE_INCLUDING_VIEWS);
    return derivedFeatures;
  }

  private static Set<Feature<?>> computeAsMapFeatures(Set<Feature<?>> multimapFeatures) {
    Set<Feature<?>> derivedFeatures = copyToSet(multimapFeatures);

  }

  private static Set<Feature<?>> computeReserializedMapFeatures(Set<Feature<?>> mapFeatures) {
    Set<Feature<?>> derivedFeatures = copyToSet(mapFeatures);
    derivedFeatures.remove(CollectionFeature.SERIALIZABLE);
    derivedFeatures.remove(CollectionFeature.SERIALIZABLE_INCLUDING_VIEWS);
    return derivedFeatures;
  }

  private static Set<Feature<?>> computeEntrySetFeatures(Set<Feature<?>> mapFeatures) {