void testGetNextResponse() {
        // When
        CommonServerMessageBlockResponse nextResponse = response.getNextResponse();

        // Then - should return null as no next response is set
        assertEquals(null, nextResponse);
    }

    @Test
    @DisplayName("Should handle prepare method correctly")
    void testPrepareMethod() {
        // Given

   */
  protected @Nullable V standardRemove(@Nullable Object key) {
    Iterator<Entry<K, V>> entryIterator = entrySet().iterator();
    while (entryIterator.hasNext()) {
      Entry<K, V> entry = entryIterator.next();
      if (Objects.equals(entry.getKey(), key)) {
        V value = entry.getValue();
        entryIterator.remove();
        return value;
      }
    }
    return null;
  }

  /**

pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards nodes which leads to next best GCD factor of 12 which provides uniform distribution.

- In this algorithm, we also make sure that we spread the drives out evenly. MinIO server expands ellipses passed as arguments. Here is a sample expansion to demonstrate the process....

            for (Iterator<Principal> ite = pr.iterator(); ite.hasNext();) {
                try {
                    KerberosPrincipal entry = (KerberosPrincipal) ite.next();
                    return entry.getRealm();
                } catch (Exception e) {
                    continue;
                }
            }
        }

        if (this.realm != null) {

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Several of these are explored in the next chapters of the tutorial.

## Order matters { #order-matters }

When creating *path operations*, you can find situations where you have a fixed path.

   */
  public static double meanOf(Iterator<? extends Number> values) {
    checkArgument(values.hasNext());
    long count = 1;
    double mean = values.next().doubleValue();
    while (values.hasNext()) {
      double value = values.next().doubleValue();
      count++;
      if (isFinite(value) && isFinite(mean)) {
        // Art of Computer Programming vol. 2, Knuth, 4.2.2, (15)

			pd.QueuedBuckets = append(pd.QueuedBuckets[:i], pd.QueuedBuckets[i+1:]...)
			// Clear tracker info.
			if pd.Bucket == bucket {
				pd.Bucket = "" // empty this out for next bucket
				pd.Prefix = "" // empty this out for the next bucket
				pd.Object = "" // empty this out for next object
			}
			return true
		}
	}
	return false
}

func (pd *PoolDecommissionInfo) isBucketDecommissioned(bucket string) bool {

     *
     * @see jcifs.internal.CommonServerMessageBlockRequest#allowChain(jcifs.internal.CommonServerMessageBlockRequest)
     */
    @Override
    public boolean allowChain(final CommonServerMessageBlockRequest next) {
        return false;
    }

    /**
     * {@inheritDoc}
     *
     * @see jcifs.internal.CommonServerMessageBlockRequest#split()
     */
    @Override

Next, it 🤖 takes the first task to finish (let's say, our "slow-file" 📝) and continues whatever it had to do with it.

	if w.nextOffset == offset {
		n, err = w.w.Write(b)
		w.nextOffset += int64(n)
	} else {
		if offset > w.nextOffset+ftpMaxWriteOffset {
			return 0, fmt.Errorf("write offset %d is too far ahead of next offset %d", offset, w.nextOffset)
		}
		w.buffer[offset] = make([]byte, len(b))
		copy(w.buffer[offset], b)
		n = len(b)
	}

again:
	nextOut, ok := w.buffer[w.nextOffset]
	if ok {