return tmp;
  }

  @Benchmark
  long parseUnsignedLong(int reps) {
    long tmp = 0;
    // Given that we make three calls per pass, we scale reps down in order
    // to do a comparable amount of work to other measurements.
    int scaledReps = reps / 3 + 1;
    for (int i = 0; i < scaledReps; i++) {
      int j = i & ARRAY_MASK;
      tmp += UnsignedLongs.parseUnsignedLong(decimalStrings[j]);

	atomic.AddUint64(&m.bytesSinceLastWindow, bytes)
}

// updateExponentialMovingAverage processes the measurements captured so far.
func (m *bucketMeasurement) updateExponentialMovingAverage(endTime time.Time) {
	// Calculate aggregate avg bandwidth and exp window avg
	m.lock.Lock()
	defer func() {
		m.startTime = endTime
		m.lock.Unlock()
	}()

	if m.startTime.IsZero() {
		return
	}

        Thread.sleep(10); // Small delay
        Instant third = MonotonicClock.now();

        assertTrue(first.isBefore(second), "Time should progress forward between measurements");
        assertTrue(second.isBefore(third), "Time should progress forward between measurements");
    }

    @Test
    @DisplayName("MonotonicClock elapsed time should increase")
    void testElapsedTime() throws InterruptedException {

 * <p>
 * This class provides precise time measurements using {@link System#nanoTime()}
 * while maintaining wall-clock time information in UTC. The wall-clock time
 * is computed from the monotonic duration since system start to ensure consistency
 * between time measurements.
 * <p>
 * This implementation is singleton-based and always uses UTC timezone. The clock

    return tmp;
  }

  @Benchmark
  long parseUnsignedLong(int reps) {
    long tmp = 0;
    // Given that we make three calls per pass, we scale reps down in order
    // to do a comparable amount of work to other measurements.
    int scaledReps = reps / 3 + 1;
    for (int i = 0; i < scaledReps; i++) {
      int j = i & ARRAY_MASK;
      tmp += UnsignedLongs.parseUnsignedLong(decimalStrings[j]);

	atomic.AddUint64(&m.bytesSinceLastWindow, bytes)
}

// updateExponentialMovingAverage processes the measurements captured so far.
func (m *rateMeasurement) updateExponentialMovingAverage(endTime time.Time) {
	// Calculate aggregate avg bandwidth and exp window avg
	m.lock.Lock()
	defer func() {
		m.startTime = endTime
		m.lock.Unlock()
	}()

	if m.startTime.IsZero() {
		return
	}

        }

        // Add to history for percentile calculation
        responseTimeHistory.addLast(responseTimeMs);
        if (responseTimeHistory.size() > 1000) { // Keep last 1000 measurements
            responseTimeHistory.removeFirst();
        }

        // Calculate moving average (simple approach)
        if (!responseTimeHistory.isEmpty()) {

        .matches("[^\\[]+\\[status=SUCCESS, result=\\[java.lang.Boolean@\\w+\\]\\]");
  }

  /**
   * This test attempts to cause a future to wait for longer than it was requested to from a timed
   * get() call. As measurements of time are prone to flakiness, it tries to assert based on ranges
   * derived from observing how much time actually passed for various operations.
   */
  @SuppressWarnings("ThreadPriorityCheck")

        .matches("[^\\[]+\\[status=SUCCESS, result=\\[java.lang.Boolean@\\w+\\]\\]");
  }

  /**
   * This test attempts to cause a future to wait for longer than it was requested to from a timed
   * get() call. As measurements of time are prone to flakiness, it tries to assert based on ranges
   * derived from observing how much time actually passed for various operations.
   */
  @SuppressWarnings("ThreadPriorityCheck")

import org.apache.maven.api.model.InputSource;
import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.BenchmarkMode;
import org.openjdk.jmh.annotations.Level;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.Mode;
import org.openjdk.jmh.annotations.OutputTimeUnit;
import org.openjdk.jmh.annotations.Scope;
import org.openjdk.jmh.annotations.Setup;
import org.openjdk.jmh.annotations.State;