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
)

## What is Erasure Code?

      r._elem.remove(testsuite._elem)
  if len(r) > 0:  # pylint: disable=g-explicit-length-test
    result += r

# Insert the number of failures for each test to help identify flakes
# need to clarify for shard
for p in result._elem.xpath(".//error | .//failure"):
  key = re.sub(r"0x\w+", "", p.getparent().get("name", "")) + p.text
  p.text = runfiles_matcher.sub("[testroot]/", p.text)

 *
 * 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()

efficiently makes your stuff load faster and saves bandwidth.

OkHttp is an HTTP client that’s efficient by default:

 * HTTP/2 support allows all requests to the same host to share a socket.
 * Connection pooling reduces request latency (if HTTP/2 isn’t available).
 * Transparent GZIP shrinks download sizes.
 * Response caching avoids the network completely for repeat requests.

   * 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;

import jcifs.internal.util.SMBUtil;
import jcifs.util.Hexdump;


/**
 * 
 * 
 */
public class SmbComNTCreateAndX extends AndXServerMessageBlock implements Request<SmbComNTCreateAndXResponse> {

    // share access specified in SmbFile

    // create disposition

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

    static final int FILE_SUPERSEDE = 0x0;

    /*