/*
     * We don't "need" to schedule a countDown() call at all here, but by doing
     * so, we come the closest we can to testing that the wait time is
     * appropriately decreased on each progressive await() call.
     */
    TimedLatch latch = new TimedLatch(/* countdownInMillis= */ LONG_DELAY_MS);
    repeatedlyInterruptTestThread(tearDownStack);
    latch.awaitUnsuccessfully(70);

    /*
     * We don't "need" to schedule a countDown() call at all here, but by doing
     * so, we come the closest we can to testing that the wait time is
     * appropriately decreased on each progressive await() call.
     */
    TimedLatch latch = new TimedLatch(/* countdownInMillis= */ LONG_DELAY_MS);
    repeatedlyInterruptTestThread(tearDownStack);
    latch.awaitUnsuccessfully(70);

        int originalSize = stopwordsFile.stopwordsItemList.size();
        StopwordsItem item = stopwordsFile.get(1).get();
        stopwordsFile.delete(item);

        // Verify the item count decreased
        // Note: get(1) may still return an item if IDs are reassigned
        assertTrue(stopwordsFile.stopwordsItemList.size() < originalSize);
    }

    // Test reload with InputStream
    @Test

  @CollectionFeature.Require(absent = SUPPORTS_ADD)
  public void testSetCount_oneToThree_unsupported() {
    assertSetCountIncreasingFailure(e3(), 3);
  }

  // Unconditional setCount size decreases:

  @CollectionSize.Require(absent = ZERO)
  @CollectionFeature.Require(SUPPORTS_REMOVE)
  public void testSetCount_oneToZero_supported() {
    assertSetCount(e0(), 0);
  }

  @CollectionFeature.Require(absent = SUPPORTS_ADD)
  public void testSetCount_oneToThree_unsupported() {
    assertSetCountIncreasingFailure(e3(), 3);
  }

  // Unconditional setCount size decreases:

  @CollectionSize.Require(absent = ZERO)
  @CollectionFeature.Require(SUPPORTS_REMOVE)
  public void testSetCount_oneToZero_supported() {
    assertSetCount(e0(), 0);
  }

 * threads. By default, this ordering is not guaranteed. However, a queue constructed with fairness
 * set to {@code true} grants threads access in FIFO order. Fairness generally decreases throughput
 * but reduces variability and avoids starvation.
 *
 * <p>This class and its iterator implement all of the optional methods of the {@link
 * Collection} and {@link Iterator} interfaces.
 *
 * @author Doug Lea

						cFns[i]()
					}
					return nil, err
				}
			}

			decReader := io.LimitReader(s2Reader, decLength)
			if decLength > compReadAheadSize {
				rah, err := readahead.NewReaderSize(decReader, compReadAheadBuffers, compReadAheadBufSize)
				if err == nil {
					decReader = rah
					cFns = append([]func(){func() {
						rah.Close()
					}}, cFns...)
				}
			}

        this.listeners = new ConcurrentHashMap<>();
        this.asyncNotifyTasks = new ConcurrentHashMap<>();
        this.scheduler = Executors.newScheduledThreadPool(3); // Increased for async notifications
        this.rpcClient = rpcClient;

        // Schedule periodic tasks
        schedulePeriodicTasks();
    }

    /**

 * threads. By default, this ordering is not guaranteed. However, a queue constructed with fairness
 * set to {@code true} grants threads access in FIFO order. Fairness generally decreases throughput
 * but reduces variability and avoids starvation.
 *
 * <p>This class and its iterator implement all of the optional methods of the {@link
 * Collection} and {@link Iterator} interfaces.
 *
 * @author Doug Lea

   *   <li>When you reduce the number of buckets, you can accept that the most recently added
   *       buckets will be removed first. More concretely, if you are dividing traffic among tasks,
   *       you can decrease the number of tasks from 15 and 10, killing off the final 5 tasks, and
   *       {@code consistentHash} will handle it. If, however, you are dividing traffic among