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);

    
    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

        String testField = "field999";

        // Warm up
        for (int i = 0; i < 100; i++) {
            queryFieldConfig.isSortField(testField);
        }

        // Measure Set-based lookup (current implementation)
        long setStartTime = System.nanoTime();
        for (int i = 0; i < 10000; i++) {
            queryFieldConfig.isSortField(testField);
        }

 * <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

Generating test coverage reports for Elasticsearch is currently not possible through Gradle.
However, it _is_ possible to gain insight in code coverage using IntelliJ's built-in coverage
analysis tool that can measure coverage upon executing specific tests. Eclipse may also be able
to do the same using the EclEmma plugin.

Test coverage reporting used to be possible with JaCoCo when Elasticsearch was using Maven

    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()) {

   * 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

        // Data: bitSize / 8 bytes
        long predictedSize = bf.bitSize() / 8 + 6;
        assertThat(bf.serializedSize()).isEqualTo(predictedSize);

        // Serialize and measure actual size
        ByteArrayOutputStream out = new ByteArrayOutputStream();
        bf.writeTo(out);
        int actualSize = out.size();
        assertThat(bf.serializedSize()).isEqualTo(actualSize);

 * may cause corruption or runtime errors if not. It may however be shared amongst multiple OkHttpClient
 * instances.
 *
 * ## Cache Optimization
 *
 * To measure cache effectiveness, this class tracks three statistics:
 *
 *  * **[Request Count:][requestCount]** the number of HTTP requests issued since this cache was
 *    created.

    RateLimiter rateLimiter = new SmoothWarmingUp(stopwatch, warmupPeriod, unit, coldFactor);
    rateLimiter.setRate(permitsPerSecond);
    return rateLimiter;
  }

  /**
   * The underlying timer; used both to measure elapsed time and sleep as necessary. A separate
   * object to facilitate testing.
   */
  private final SleepingStopwatch stopwatch;