private void weaklyReferenceQueue() {
    frq = new FinalizableReferenceQueue();
    queueReference = new WeakReference<>(frq.queue);

    /*
     * Queue and clear a reference for good measure. We test later on that
     * the finalizer thread stopped, but we should test that it actually
     * started first.
     */
    reference =
        new FinalizableWeakReference<Object>(new Object(), frq) {

			return
		}
	}
}

func (r *ReplicationStats) updateMovingAvg() {
	r.RLock()
	for _, s := range r.Cache {
		for _, st := range s.Stats {
			st.XferRateLrg.measure.updateExponentialMovingAverage(time.Now())
			st.XferRateSml.measure.updateExponentialMovingAverage(time.Now())
		}
	}
	r.RUnlock()
}

// ActiveWorkers returns worker stats
func (r *ReplicationStats) ActiveWorkers() ActiveWorkerStat {

          if ((hash1 & (1 << k)) == (hash2 & (1 << k))) {
            same[k] += 1;
          } else {
            diff[k] += 1;
          }
        }
      }
      // measure probability and assert it's within margin of error
      for (int j = 0; j < hashBits; j++) {
        double prob = (double) diff[j] / (double) (diff[j] + same[j]);
        assertThat(prob).isWithin(epsilon).of(0.50d);

      if (contentType != null) {
        sink
          .writeUtf8("Content-Type: ")
          .writeUtf8(contentType.toString())
          .write(CRLF)
      }

      // We can't measure the body's size without the sizes of its components.
      val contentLength = body.contentLength()
      if (contentLength == -1L && countBytes) {
        byteCountBuffer!!.clear()
        return -1L
      }

    
    SmbFile file = new SmbFile("smb://server/share/largefile.dat", context);
    
    // Measure single channel throughput
    long singleChannelTime = measureReadTime(file, false);
    
    // Measure multi-channel throughput
    long multiChannelTime = measureReadTime(file, true);
    
    // Multi-channel should be faster

          if ((hash1 & (1 << k)) == (hash2 & (1 << k))) {
            same[k] += 1;
          } else {
            diff[k] += 1;
          }
        }
      }
      // measure probability and assert it's within margin of error
      for (int j = 0; j < hashBits; j++) {
        double prob = (double) diff[j] / (double) (diff[j] + same[j]);
        assertThat(prob).isWithin(epsilon).of(0.50d);

   * underlying model is a continuous function mapping storedPermits (from 0.0 to maxStoredPermits)
   * onto the 1/rate (i.e. intervals) that is effective at the given storedPermits. "storedPermits"
   * essentially measure unused time; we spend unused time buying/storing permits. Rate is
   * "permits / time", thus "1 / rate = time / permits". Thus, "1/rate" (time / permits) times

 * <p>A high-quality hash function strives for some subset of the following virtues:
 *
 * <ul>
 *   <li><b>collision-resistant:</b> while the definition above requires making at least <i>some</i>
 *       token attempt, one measure of the quality of a hash function is <i>how well</i> it succeeds
 *       at this goal. Important note: it may be easy to achieve the theoretical minimum collision

 * <p>A high-quality hash function strives for some subset of the following virtues:
 *
 * <ul>
 *   <li><b>collision-resistant:</b> while the definition above requires making at least <i>some</i>
 *       token attempt, one measure of the quality of a hash function is <i>how well</i> it succeeds
 *       at this goal. Important note: it may be easy to achieve the theoretical minimum collision

    CIFSContext context = getTestContext();
    context.getConfig().setProperty("jcifs.smb.client.useRDMA", "true");
    
    SmbFile file = new SmbFile("smb://server/share/largefile.dat", context);
    
    // Measure RDMA transfer performance
    byte[] data = new byte[10485760];  // 10MB
    Arrays.fill(data, (byte)0x42);
    
    long start = System.currentTimeMillis();
    
    try (OutputStream os = file.getOutputStream()) {