import jcifs.internal.util.SMBUtil;

/**
 * DFS (Distributed File System) referral response buffer parser.
 * Decodes server responses to DFS referral requests, extracting information about
 * available DFS targets, path consumption details, and referral flags.
 *
 * @author mbechler
 */
public class DfsReferralResponseBuffer implements Decodable {

    /**
     * Default constructor for DfsReferralResponseBuffer.

 * control. Under low update contention, the two classes have similar characteristics. But under
 * high contention, expected throughput of this class is significantly higher, at the expense of
 * higher space consumption.
 *
 * <p>This class extends {@link Number}, but does not define methods such as {@code
 * equals}, {@code hashCode} and {@code compareTo} because instances are expected to be mutated, and

	healStoppedStatus                      = "stopped"
	healFinishedStatus                     = "finished"
)

const (
	// a heal sequence with this many un-consumed heal result
	// items blocks until heal-status consumption resumes or is
	// aborted due to timeout.
	maxUnconsumedHealResultItems = 1000

	// if no heal-results are consumed (via the heal-status API)
	// for this timeout duration, the heal sequence is aborted.

         * than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *

 *
 * <p>This class should not be assumed to be universally superior to {@code
 * java.util.LinkedHashSet}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */

         * than a handful of exceptions. But it seems prudent to set a cap on how many we'll cache.
         * This avoids out-of-control memory consumption, and it keeps the cache from growing so
         * large that doing the lookup is noticeably slower than redoing the work would be.
         *

      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;
      long now = System.nanoTime();
      if (nanos == 0 || now - nanos >= 0) {

      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;
      long now = System.nanoTime();
      if (nanos == 0 || now - nanos >= 0) {

This was changed in version 0.110.0 to fix unhandled memory consumption from forwarded exceptions without a handler (internal server errors), and to make it consistent with the behavior of regular Python code.

 * guarantees.
 *
 * <p>This class should not be assumed to be universally superior to {@code java.util.HashMap}.
 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 * @author Jon Noack
 */