} else if (i % DIRECT_EXECUTIONS_PER_THREAD == DIRECT_EXECUTIONS_PER_THREAD - 1) {
          // When at max depth, record stack trace depth
          lengthChecks.add(
              serializer.submit(
                  new Callable<Integer>() {
                    @Override
                    public Integer call() {
                      holder.count++;
                      return Thread.currentThread().getStackTrace().length;

        } else if (i % DIRECT_EXECUTIONS_PER_THREAD == DIRECT_EXECUTIONS_PER_THREAD - 1) {
          // When at max depth, record stack trace depth
          lengthChecks.add(
              serializer.submit(
                  new Callable<Integer>() {
                    @Override
                    public Integer call() {
                      holder.count++;
                      return Thread.currentThread().getStackTrace().length;

            }
        }
        if (nThreads < 1) {
            nThreads = 1;
        }
        final ExecutorService executorService = new ThreadPoolExecutor(nThreads, nThreads, 0L, TimeUnit.MILLISECONDS,
                new LinkedBlockingQueue<Runnable>(nThreads), new ThreadPoolExecutor.CallerRunsPolicy());
        try {
            while (!isInterrupted() && !stopIfLeisure()) {

   * accommodate as many threads as will ever concurrently modify the table. Using a significantly
   * higher value than you need can waste space and time, and a significantly lower value can lead
   * to thread contention. But overestimates and underestimates within an order of magnitude do not
   * usually have much noticeable impact. A value of one permits only one thread to modify the map

 * possibly run in another thread. That cause should itself be an {@code Error}; if not, use {@code
 * ExecutionException} or {@link UncheckedExecutionException}. This allows the client code to
 * continue to distinguish between exceptions and errors, even when they come from other threads.
 *
 * @author Chris Povirk
 * @since 10.0
 */
@GwtCompatible

                // Explicitly yield to increase the probability of a pathological scheduling.
                Thread.yield();
                return new Schedule(0, SECONDS);
              }
            };
          }
        };
    service.useBarriers = false;
    service.startAsync().awaitRunning();
    Thread.sleep(50);
    service.useBarriers = true;
    service.firstBarrier.await();

            });
    assertFalse(task.isDone());
    Thread thread =
        new Thread(
            new Runnable() {
              @Override
              public void run() {
                try {
                  task.run();
                } finally {
                  exitLatch.countDown();
                }
              }
            });
    thread.start();
    enterLatch.await();

 * {@link Map} specified in the {@link Table} interface.
 *
 * <p>Note that this implementation is not synchronized. If multiple threads access this table
 * concurrently and one of the threads modifies the table, it must be synchronized externally.
 *
 * <p>See the Guava User Guide article on <a href=

    assertFalse(future.isDone());
    assertFalse(future.isCancelled());

    CountDownLatch successLatch = new CountDownLatch(1);

    // Run cancellation in a separate thread as an extra thread-safety test.
    new Thread(
            () -> {
              assertThrows(CancellationException.class, future::get);
              successLatch.countDown();
            })
        .start();

   */
  internal var interceptorScopedExchange: Exchange? = null
    private set

  // These properties are guarded by [lock]. They are typically only accessed by the thread executing
  // the call, but they may be accessed by other threads for duplex requests.

  /** True if this call still has a request body open. */
  private var requestBodyOpen = false

  /** True if this call still has a response body open. */