// streams. Buffers are retained in a deque so that there's no copying between buffers while
    // reading and so all of the bytes in each new allocated buffer are available for reading from
    // the stream.
    for (int bufSize = initialBufferSize;
        totalLen < MAX_ARRAY_LEN;
        bufSize = IntMath.saturatedMultiply(bufSize, bufSize < 4096 ? 4 : 2)) {

     * builds an empty map.
     *
     * <p>If the {@code resolve} parameter value is {@code false}, then some or all map values may
     * be null instead of the actual module name. This option can avoid the cost of reading module
     * descriptors when only the modules existence needs to be verified.</p>
     *
     * <p><b>Algorithm:</b>
     * If the given path is a directory, then there is a choice:
     * </p>
     * <ul>

   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.
   *

                }
              } finally {
                /*
                 * "null" means: There is no need to access `futures` again during
                 * `processCompleted` because we're reading each value during a call to
                 * handleOneInputDone.
                 */
                decrementCountAndMaybeComplete(null);
              }
            },
            directExecutor());
      }

       * use the `endpoint` field, compareTo() and endpoint(). Additionally, the main implementation
       * of Cut.compareTo checks for belowAll before reading accessing `endpoint` on another Cut
       * instance.
       */
      super("");
    }

    @Override
    Comparable<?> endpoint() {
      throw new IllegalStateException("range unbounded on this side");

     * bytecode rewriting that checks for any null value that passes through an API with a
     * known-non-null type? But that particular problem might not arise here, since we're not
     * actually reading from the fields in any case in which they might be null (as proven by the
     * requireNonNull checks below). Plus, we're *already* lying here, since newHeader passes a null

  @GwtIncompatible // java.io.ObjectInputStream
  private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException {
    stream.defaultReadObject();
    @SuppressWarnings("unchecked")
    // reading data stored by writeObject
    Comparator<? super E> comparator = (Comparator<? super E>) requireNonNull(stream.readObject());
    Serialization.getFieldSetter(AbstractSortedMultiset.class, "comparator").set(this, comparator);

  }

  /**
   * Used to randomize {@link #goodFastHash} instances, so that programs which persist anything
   * dependent on the hash codes they produce will fail sooner.
   */
  @SuppressWarnings("GoodTime") // reading system time without TimeSource
  static final int GOOD_FAST_HASH_SEED = (int) System.currentTimeMillis();

  /**
   * Returns a hash function implementing the <a

                    } else if (StringUtil.isBlank(reading) && StringUtil.isBlank(boost)) {
                        elevateWordBhv.delete(elevateWord);
                        final String id = elevateWord.getId();
                        elevateWordToLabelBhv.queryDelete(cb -> cb.query().setElevateWordId_Equal(id));
                    } else {
                        elevateWord.setReading(reading);

   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.
   *