assertThrows(
            TimeoutException.class, () -> service.startAsync().awaitRunning(1, MILLISECONDS));
    assertThat(e)
        .hasMessageThat()
        .isEqualTo("Timed out waiting for Foo [STARTING] to reach the RUNNING state.");
  }

  private static class TestService extends AbstractIdleService {
    int startUpCalled = 0;
    int shutDownCalled = 0;
    final List<State> transitionStates = Lists.newArrayList();

   * free slot.
   *
   * The table size is capped because, when there are more threads
   * than CPUs, supposing that each thread were bound to a CPU,
   * there would exist a perfect hash function mapping threads to
   * slots that eliminates collisions. When we reach capacity, we
   * search for this mapping by randomly varying the hash codes of
   * colliding threads.  Because search is random, and collisions

      // even check the guard. I don't think we care too much about this use case but it could lead
      // to a confusing error message.
      throw new TimeoutException("Timed out waiting for " + this + " to reach the RUNNING state.");
    }
  }

  @Override
  public final void awaitTerminated() {
    monitor.enterWhenUninterruptibly(isStopped);
    try {
      checkCurrentState(TERMINATED);
    } finally {

    } else {
      frameCallback.onReadMessage(messageFrameBuffer.readByteString())
    }
  }

  /** Read headers and process any control frames until we reach a non-control frame. */
  @Throws(IOException::class)
  private fun readUntilNonControlFrame() {
    while (!closed) {
      readHeader()
      if (!isControlFrame) {
        break
      }

storage class by setting `x-amz-storage-class=STANDARD/REDUCED_REDUNDANCY` for each object uploads so effectively utilizing the capacity of the cluster. Additionally these can also be enforced using IAM policies to make sure the client uploads with correct HTTP headers.

- MinIO also supports expansion of existing clusters in server pools. Each pool is a self contained entity with same SLA's (read/write quorum) for each object as original cluster. By using the existing namespace for lookup validation...

   * reduced the available size of the buffer each time a call to read didn't fill up the available
   * space in the buffer completely. In general this is a performance problem since the buffer size
   * is permanently reduced, but with certain Reader implementations it could also cause the buffer
   * size to reach 0, causing an infinite loop.
   */

   * reduced the available size of the buffer each time a call to read didn't fill up the available
   * space in the buffer completely. In general this is a performance problem since the buffer size
   * is permanently reduced, but with certain Reader implementations it could also cause the buffer
   * size to reach 0, causing an infinite loop.
   */

      hashTableKToV[keyBucket] = dest;
    } else {
      int prevInBucket = hashTableKToV[keyBucket];
      for (int entryInBucket = nextInBucketKToV[prevInBucket];
          /* should never reach end */ ;
          entryInBucket = nextInBucketKToV[entryInBucket]) {
        if (entryInBucket == src) {
          nextInBucketKToV[prevInBucket] = dest;
          break;
        }

        assertThrows(
            TimeoutException.class, () -> service.startAsync().awaitRunning(1, MILLISECONDS));
    assertThat(e)
        .hasMessageThat()
        .isEqualTo("Timed out waiting for Foo [STARTING] to reach the RUNNING state.");
  }

  private class FakeService extends AbstractExecutionThreadService implements TearDown {

    private final ExecutorService executor = Executors.newSingleThreadExecutor();

          } else if (endOfInput) { // (b)
            doneEncoding = true;
          } else { // (c)
            readMoreChars();
          }
        } else if (result.isError()) {
          // Only reach here if a CharsetEncoder with non-REPLACE settings is used.
          result.throwException();
          return 0; // Not called.
        }
      }
    }
  }