n++;
                int size = chain.size();
                int cost = chain.getCreditCost();
                CommonServerMessageBlockRequest next = chain.getNext();
                if ( log.isTraceEnabled() ) {
                    log.trace(
                        String.format("%s costs %d avail %d (%s)", chain.getClass().getName(), cost, this.credits.availablePermits(), this.name));
                }

    }
    sink1.writeUtf8("def")
    sink1.close()
    assertFailsWith<ConnectionShutdownException> {
      connection.newStream(headerEntries("c", "cola"), true)
    }
    assertThat(stream1.isOpen).isTrue()
    assertThat(stream2.isOpen).isFalse()
    assertThat(connection.openStreamCount()).isEqualTo(1)

    // Verify the peer received what was expected.

   * E} is an {@link Enum} type, use {@link EnumSet#noneOf} instead. Otherwise, strongly consider
   * using a {@code LinkedHashSet} instead, at the cost of increased memory footprint, to get
   * deterministic iteration behavior.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated. Instead,

				"application/vnd.openxmlformats-officedocument.wordprocessingml.document",
				"application/vnd.openxmlformats-officedocument.wordprocessingml.template",
				"application/vnd.osa.netdeploy",
				"application/vnd.osgi.bundle",
				"application/vnd.osgi.dp",
				"application/vnd.otps.ct-kip+xml",
				"application/vnd.palm",
				"application/vnd.paos.xml",
				"application/vnd.pg.format",

  // safely publish these objects and we won't need this whole discussion.
  // TODO(user,lukes): consider adding volatile to all these fields since in current known JVMs
  // that should resolve the issue. This comes at the cost of adding more write barriers to the
  // implementations.

  private Futures() {}

  /**
   * Creates a {@code ListenableFuture} which has its value set immediately upon construction. The

		fileName = part.FileName()

		// Multiple values for the same key (one map entry, longer slice) are cheaper
		// than the same number of values for different keys (many map entries), but
		// using a consistent per-value cost for overhead is simpler.
		maxMemoryBytes := 2 * int64(10<<20)
		maxMemoryBytes -= int64(len(name))
		maxMemoryBytes -= mapEntryOverhead
		if maxMemoryBytes < 0 {

    return new MergingIterator<>(iterators, comparator);
  }

  /**
   * An iterator that performs a lazy N-way merge, calculating the next value each time the iterator
   * is polled. This amortizes the sorting cost over the iteration and requires less memory than
   * sorting all elements at once.
   *
   * <p>Retrieving a single element takes approximately O(log(M)) time, where M is the number of

  // safely publish these objects and we won't need this whole discussion.
  // TODO(user,lukes): consider adding volatile to all these fields since in current known JVMs
  // that should resolve the issue. This comes at the cost of adding more write barriers to the
  // implementations.

  private Futures() {}

  /**
   * Creates a {@code ListenableFuture} which has its value set immediately upon construction. The

   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,

   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,