*/
  @CanIgnoreReturnValue
  @Override
  public int setCount(E element, int count) {
    checkNotNull(element);
    checkNonnegative(count, "count");
    while (true) {
      AtomicInteger existingCounter = safeGet(countMap, element);
      if (existingCounter == null) {
        if (count == 0) {
          return 0;
        } else {

 * of the crawler's behavior.
 *
 * <p>
 * The context includes information such as the session ID, active thread count, access count, crawler status,
 * URL filter, rule manager, interval controller, robots.txt URL set, sitemaps, number of threads,
 * maximum thread check count, maximum depth, and maximum access count.
 * </p>
 *
 * <p>

   */
  @CanIgnoreReturnValue
  @Override
  public int setCount(E element, int count) {
    checkNotNull(element);
    checkNonnegative(count, "count");
    while (true) {
      AtomicInteger existingCounter = safeGet(countMap, element);
      if (existingCounter == null) {
        if (count == 0) {
          return 0;
        } else {

    }

    @Test
    @DisplayName("Test run method")
    void testRunMethod() throws Exception {
        AtomicInteger counter = new AtomicInteger(0);

        circuitBreaker.run(() -> counter.incrementAndGet());
        assertEquals(1, counter.get());

        SimpleCircuitBreaker.Statistics stats = circuitBreaker.getStatistics();
        assertEquals(1, stats.totalCalls);

                    return (int) misses.incrementAndGet();
                  }
                });

    // To start, fill up the cache.
    // Each miss both increments the counter and causes the map to grow by one,
    // so until evictions begin, the size of the map is the greatest return
    // value seen so far
    while (cache.getUnchecked(nextRandomKey()) < maximumSize) {}

    requests.set(0);

                    return (int) misses.incrementAndGet();
                  }
                });

    // To start, fill up the cache.
    // Each miss both increments the counter and causes the map to grow by one,
    // so until evictions begin, the size of the map is the greatest return
    // value seen so far
    while (cache.getUnchecked(nextRandomKey()) < maximumSize) {}

    requests.set(0);

            final int maxDepth = getMaxDepth(paramMap, dataMap);
            long counter = 0;
            final Deque<CrawlRequest> requestQueue = new LinkedList<>();
            final Set<String> processedUrls = new HashSet<>();
            requestQueue.offer(new CrawlRequest(url, 0));
            while (!requestQueue.isEmpty() && (maxAccessCount < 0 || counter < maxAccessCount)) {
                final CrawlRequest crawlRequest = requestQueue.poll();

	}

	maxima = 0 // Counter for remembering max occurrence of elements.
	latest := int64(0)

	// Find the common cardinality from previously collected
	// occurrences of elements.
	for nano, count := range timeOccurrenceMap {
		if count < maxima {
			continue
		}

		// We are at or above maxima
		if count > maxima || nano > latest {
			maxima = count
			latest = nano
		}
	}

    private static final java.util.concurrent.ConcurrentLinkedQueue<byte[]> bufferQueue =
            new java.util.concurrent.ConcurrentLinkedQueue<>();

    // Track queue size with atomic counter for efficiency
    private static final java.util.concurrent.atomic.AtomicInteger queueSize = new java.util.concurrent.atomic.AtomicInteger(0);

    /**

   * exception is thrown, this exception is used as the result of the output {@code Future}.
   *
   * <p>Usage example:
   *
   * {@snippet :
   * // Falling back to a zero counter in case an exception happens when processing the RPC to fetch
   * // counters.
   * ListenableFuture<Integer> faultTolerantFuture =
   *     fetchCounters().catching(FetchException.class, x -> 0, directExecutor());
   * }
   *