*/
        Runnable localTask = requireNonNull(task);
        task = null;
        localTask.run();
        return;
      }
      // Executor called reentrantly! Make sure that further calls don't overflow stack. Further
      // reentrant calls will see that their current thread is the same as the one set in
      // latestTaskQueue, and queue rather than calling execute() directly.

    }

  private fun gzip(data: ByteArray): Buffer {
    val buffer = Buffer()
    GzipSink(buffer).buffer().write(data).close()
    return buffer
  }

  /** Create a sufficiently large header set to overflow INITIAL_MAX_FRAME_SIZE bytes.  */
  private fun largeHeaders(): List<Header> {
    val nameValues = arrayOfNulls<String>(32)
    val chars = CharArray(512)
    var i = 0
    while (i < nameValues.size) {

   * 1}, this method has the identical effect to {@link #add(Object)}. This method is functionally
   * equivalent (except in the case of overflow) to the call {@code
   * addAll(Collections.nCopies(element, occurrences))}, which would presumably perform much more
   * poorly.
   *

  }

  /** There's no reason for the queueSize to ever be more than maxSize + 1 */
  private static int capAtMaximumSize(int queueSize, int maximumSize) {
    return min(queueSize - 1, maximumSize) + 1; // don't overflow
  }

        void testLargeMidValue() {
            long largeMid = Long.MAX_VALUE;
            testMessage.setMid(largeMid);
            assertEquals(largeMid, testMessage.getMid());

            // HashCode should handle overflow correctly
            int hash = testMessage.hashCode();
            assertEquals((int) largeMid, hash);
        }

        @Test
        @DisplayName("Should handle negative status codes")

      /*
       * It speeds things up considerably to unconditionally add count to totalCount here,
       * but that destroys failure atomicity in the case of count overflow. =(
       */
      int cmp = comparator.compare(e, getElement());
      if (cmp < 0) {
        AvlNode<E> initLeft = left;
        if (initLeft == null) {
          result[0] = 0;

      setFutureSuccess.set(false);
      cancellationSuccess.set(false);
      finalResults.clear();
    }
    executor.shutdown();
  }

  // In a previous implementation this would cause a stack overflow after ~2000 futures chained
  // together.  Now it should only be limited by available memory (and time)
  public void testSetFuture_stackOverflow() {
    SettableFuture<String> orig = SettableFuture.create();

  }

  /** There's no reason for the queueSize to ever be more than maxSize + 1 */
  private static int capAtMaximumSize(int queueSize, int maximumSize) {
    return min(queueSize - 1, maximumSize) + 1; // don't overflow
  }

      int adjust = size() - 1;
      for (int i = 0; i < axes.size(); i++) {
        adjust *= 31;
        adjust = ~~adjust;
        // in GWT, we have to deal with integer overflow carefully
      }
      int hash = 1;
      for (Set<E> axis : axes) {
        hash = 31 * hash + (size() / axis.size() * axis.hashCode());

        hash = ~~hash;
      }
      hash += adjust;

    i = 1 << 30;
    assertFalse(MinMaxPriorityQueue.isEvenLevel(i - 2));
    assertTrue(MinMaxPriorityQueue.isEvenLevel(i - 1));
    assertTrue(MinMaxPriorityQueue.isEvenLevel(i));

    // 1 << 31 is negative because of overflow, 1 << 31 - 1 is positive
    // since isEvenLevel adds 1, we need to do - 2.
    assertTrue(MinMaxPriorityQueue.isEvenLevel((1 << 31) - 2));
    assertTrue(MinMaxPriorityQueue.isEvenLevel(Integer.MAX_VALUE - 1));