There's a high chance that the logic for your *startup* and *shutdown* is connected, you might want to start something and then finish it, acquire a resource and then release it, etc.

Doing that in separated functions that don't share logic or variables together is more difficult as you would need to store values in global variables or similar tricks.

Because of that, it's now recommended to instead use the `lifespan` as explained above.

 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 */

package jcifs.smb1.smb1;

import jcifs.smb1.util.Hexdump;

class SmbComNTCreateAndX extends AndXServerMessageBlock {

    // share access specified in SmbFile

    // create disposition

    /* Creates a new file or supersedes the existing one
     */

    static final int FILE_SUPERSEDE    = 0x0;

            }
            if (path == null) {
                path = System.getenv("path");
            }
            final List<String> pathList = new ArrayList<>();
            pathList.add("/usr/share/fess/bin");
            if (path != null) {
                stream(path.split(File.pathSeparator)).of(stream -> stream.map(String::trim).forEach(s -> pathList.add(s)));
            }
            if (logger.isDebugEnabled()) {

            p++;
        }
        while ( p < len && pathInfo.charAt(p) == '/' ) {
            p++;
        }
        if ( p < len ) { /* then there must be a share */
            out[ i++ ] = '/';
            do { /* collect the share name */
                out[ i++ ] = ( ch = pathInfo.charAt(p++) );
            }
            while ( p < len && ch != '/' );
        }
        return new String(out, 0, i);

	metacacheBlockSize = 5000

	// metacacheSharePrefix controls whether prefixes on dirty paths are always shared.
	// This will make `test/a` and `test/b` share listings if they are concurrent.
	// Enabling this will make cache sharing more likely and cause less IO,
	// but may cause additional latency to some calls.
	metacacheSharePrefix = false
)

      return samples;
    }

    @Override
    public Set<V> create(Object... elements) {
      @SuppressWarnings("unchecked")
      V[] valuesArray = (V[]) elements;

      // Start with a suitably shaped collection of entries
      Collection<Entry<K, V>> originalEntries = mapGenerator.getSampleElements(elements.length);

      // Create a copy of that, with the desired value for each value

 *
 * The task runner is also responsible for releasing held threads when the library is unloaded.
 * This is for the benefit of container environments that implement code unloading.
 *
 * Most applications should share a process-wide [TaskRunner] and use queues for per-client work.
 */
class TaskRunner(
  val backend: Backend,
  internal val logger: Logger = TaskRunner.logger,
) {
  val lock: ReentrantLock = ReentrantLock()

/**
 * A set of tasks that are executed in sequential order.
 *
 * Work within queues is not concurrent. This is equivalent to each queue having a dedicated thread
 * for its work; in practice a set of queues may share a set of threads to save resources.
 */
class TaskQueue internal constructor(
  internal val taskRunner: TaskRunner,
  internal val name: String,
) {
  val lock: ReentrantLock = ReentrantLock()

   * 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.
   *
   * In part because Cells are relatively large, we avoid creating

                dr.server = resp.referrals[di].path.substring(1).toLowerCase();
            } else {
                dfsPathSplit(resp.referrals[di].node, arr);
                dr.server = arr[1];
                dr.share = arr[2];
                dr.path = arr[3];
            }
            dr.pathConsumed = resp.pathConsumed;

            di++;
            if (di == rn)
                break;