* we change the rate.
   */
  public void testWeNeverGetABurstMoreThanOneSec() {
    RateLimiter limiter = RateLimiter.create(1.0, stopwatch);
    int[] rates = {1000, 1, 10, 1000000, 10, 1};
    for (int rate : rates) {
      int oneSecWorthOfWork = rate;
      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);

   * we change the rate.
   */
  public void testWeNeverGetABurstMoreThanOneSec() {
    RateLimiter limiter = RateLimiter.create(1.0, stopwatch);
    int[] rates = {1000, 1, 10, 1000000, 10, 1};
    for (int rate : rates) {
      int oneSecWorthOfWork = rate;
      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);

	BandWidthLimitInBytesPerSecond int64 `json:"limitInBits"`
	// current bandwidth reported
	CurrentBandwidthInBytesPerSecond float64 `json:"currentBandwidth"`
	// transfer rate for large uploads
	XferRateLrg *XferStats `json:"-" msg:"lt"`
	// transfer rate for small uploads
	XferRateSml *XferStats `json:"-" msg:"st"`

	// Deprecated fields
	// Pending size in bytes
	PendingSize int64 `json:"pendingReplicationSize"`

        // Test rate at exactly 1000000 (1 MB/s)
        builder = new DefaultMessageBuilder();
        format.formatRate(builder, 1000000.0);
        assertEquals("1.0 MB/s", builder.build());
    }

    @Test
    void testFormatRateLargeValues() {
        FileSizeFormat format = new FileSizeFormat();

        // Test large but valid rates

 * <p>Rate limiters are often used to restrict the rate at which some physical or logical resource
 * is accessed. This is in contrast to {@link java.util.concurrent.Semaphore} which restricts the
 * number of concurrent accesses instead of the rate (note though that concurrency and rate are
 * closely related, e.g. see <a href="http://en.wikipedia.org/wiki/Little%27s_law">Little's
 * Law</a>).
 *

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import jcifs.smb.SmbException;

/**
 * Rate limiter for authentication attempts to prevent brute force attacks.
 *
 * Features:
 * - Per-account rate limiting
 * - Per-IP rate limiting
 * - Global rate limiting
 * - Exponential backoff for repeated failures
 * - Account lockout after threshold
 * - Automatic cleanup of old entries
 */

        // Make many attempts to trigger global rate limit
        for (int i = 1; i <= 20; i++) {
            assertTrue(rateLimiter.checkAttempt("user" + i, "192.168.1." + i), "Attempt " + i + " should be allowed");
        }

        // 21st attempt should be blocked by global rate limit
        assertFalse(rateLimiter.checkAttempt("user21", "192.168.1.21"), "Should block after global rate limit");
    }

    @Test

   * 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

 *       thoroughly as possible.
 *   <li><b>bit-dispersing:</b> masking out any <i>single bit</i> from a hash code should yield only
 *       the expected <i>twofold</i> increase to all collision rates. Informally, the "information"
 *       in the hash code should be as evenly "spread out" through the hash code's bits as possible.
 *       The result is that, for example, when choosing a bucket in a hash table of size 2^8,

    }

    /**
     * Increment error counter
     */
    public void incrementErrors() {
        errors.incrementAndGet();
    }

    /**
     * Get error rate (errors / total requests)
     *
     * @return error rate between 0.0 and 1.0
     */
    public double getErrorRate() {
        long total = requestsSent.get();
        if (total == 0)
            return 0.0;