* @param value any {@code long} value
   * @return the same value cast to {@code short} if it is in the range of the {@code short} type,
   *     {@link Short#MAX_VALUE} if it is too large, or {@link Short#MIN_VALUE} if it is too small
   */
  public static short saturatedCast(long value) {
    if (value > Short.MAX_VALUE) {
      return Short.MAX_VALUE;
    }
    if (value < Short.MIN_VALUE) {
      return Short.MIN_VALUE;
    }

                }
            }
        }
        return containingFailures
    }

    /**
     * After archiving the test files, do a cleanup to get rid of TeamCity "XX published a lot of small artifacts" warning.
     */
    private
    fun cleanUp(filesToCleanUp: Collection<File>) {
        try {
            fileSystemOperations.delete {
                delete(*filesToCleanUp.toTypedArray())

   changing `.java` files.

 * **Kotlin source compatibility** is the ability to upgrade Kotlin uses of OkHttp 3.x to 4.x
   without changing `.kt` files.

With a few small exceptions (below), OkHttp 4.x is both binary- and Java source-compatible with
OkHttp 3.x. You can use an OkHttp 4.x .jar file with applications or libraries built for OkHttp 3.x.

    var finished: Boolean = false,
  ) : Sink {
    /**
     * Buffer of outgoing data. This batches writes of small writes into this sink as larges frames
     * written to the outgoing connection. Batching saves the (small) framing overhead.
     */
    private val sendBuffer = Buffer()

    /** Trailers to send at the end of the stream. */
    var trailers: Headers? = null

        ComponentUtil.setFessConfig(new MockFessConfig() {
            @Override
            public Integer getCookieSearchParameterMaxLengthAsInteger() {
                return 10; // Very small limit
            }
        });

        String longValue = "a".repeat(1000);
        getMockRequest().setParameter("q", longValue);

        searchHelper.storeSearchParameters();

  /** Default size of a compact hash-based collection. */
  static final int DEFAULT_SIZE = 3;

  /**
   * Minimum size of the hash table of a compact hash-based collection. Because small hash tables
   * use a byte[], any smaller size uses the same amount of memory due to object padding.
   */
  private static final int MIN_HASH_TABLE_SIZE = 4;

  require(millis != 0L || duration <= 0L) { "$name too small" }
  return millis.toInt()
}

internal fun checkDuration(
  name: String,
  duration: Duration,
): Int {
  check(!duration.isNegative()) { "$name < 0" }
  val millis = duration.inWholeMilliseconds
  require(millis <= Integer.MAX_VALUE) { "$name too large" }
  require(millis != 0L || !duration.isPositive()) { "$name too small" }
  return millis.toInt()
}

  // Timed Get
  // There are a few design constraints to consider
  // * We want to be responsive to small timeouts, unpark() has non trivial latency overheads (I
  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of

            return entity;
        });
    }

    // ===================================================================================
    //                                                                        Small Helper
    //                                                                        ============
    //                                                                              JSP

    ImmutableSet.Builder<Double> fractionalBuilder = ImmutableSet.builder();
    integralBuilder.addAll(Doubles.asList(0.0, -0.0, Double.MAX_VALUE, -Double.MAX_VALUE));
    // Add small multiples of MIN_VALUE and MIN_NORMAL
    for (int scale = 1; scale <= 4; scale++) {
      for (double d : Doubles.asList(Double.MIN_VALUE, Double.MIN_NORMAL)) {
        fractionalBuilder.add(d * scale).add(-d * scale);