*/
  public double expectedFpp() {
    return Math.pow((double) bits.bitCount() / bitSize(), numHashFunctions);
  }

  /**
   * Returns an estimate for the total number of distinct elements that have been added to this
   * Bloom filter. This approximation is reasonably accurate if it does not exceed the value of
   * {@code expectedInsertions} that was used when constructing the filter.
   *

        final String permissionKey = userBean.map(user -> StreamUtil.stream(user.getPermissions())
                .get(stream -> stream.sorted().distinct().collect(Collectors.joining("\n")))).orElse(StringUtil.EMPTY);

        try {
            return facetCache.get(query + "\n" + permissionKey, () -> {

      // extra zero bits we need to add to the end of bitsPerChar to get 3 in total.
      // The logic here would be wrong for bitsPerChar > 8, but since we require distinct ASCII
      // characters that can't happen.
      int zeroesInBitsPerChar = Integer.numberOfTrailingZeros(bitsPerChar);
      this.charsPerChunk = 1 << (3 - zeroesInBitsPerChar);

   * href="http://en.wikipedia.org/wiki/Adobe_Photoshop#File_format">Wikipedia</a>; this is the
   * regular output/input of Photoshop (which can also export to various image formats; note that
   * files with extension "PSB" are in a distinct but related format).
   *
   * <p>This is a more recent replacement for the older, experimental type {@code x-photoshop}: <a
   * href="http://tools.ietf.org/html/rfc2046#section-6">RFC-2046.6</a>.
   *
   * @since 15.0

   * It will never change, even if the maps change at a later time.
   *
   * <p>Since this method uses {@code TreeMap} instances internally, the keys of the right map must
   * all compare as distinct according to the comparator of the left map.
   *
   * <p><b>Note:</b>If you only need to know whether two sorted maps have the same mappings, call
   * {@code left.equals(right)} instead of this method.
   *

   * loading the value for this key, simply waits for that thread to finish and returns its loaded
   * value. Note that multiple threads can concurrently load values for distinct keys.
   *
   * <p>This method does not alter the state of this {@code CacheBuilder} instance, so it can be
   * invoked again to create multiple independent caches.
   *

            if (i > 0 && comparator.compare((K) sortedKeys[i - 1], (K) sortedKeys[i]) == 0) {
              throw new IllegalArgumentException(
                  "keys required to be distinct but compared as equal: "
                      + sortedKeys[i - 1]
                      + " and "
                      + sortedKeys[i]);
            }

   * loading the value for this key, simply waits for that thread to finish and returns its loaded
   * value. Note that multiple threads can concurrently load values for distinct keys.
   *
   * <p>This method does not alter the state of this {@code CacheBuilder} instance, so it can be
   * invoked again to create multiple independent caches.
   *

//  fn_name - the name of the new TF_Function. Should match the operation
//            name (OpDef.name) regexp [A-Z][A-Za-z0-9_.\\-/]*.
//            If `append_hash_to_fn_name` is false, `fn_name` must be distinct
//            from other function and operation names (at least those
//            registered in graphs where this function will be used).
//  append_hash_to_fn_name - Must be 0 or 1. If set to 1, the actual name

    assertThat((response1.receivedResponseAtMillis - t0).toDouble()).isCloseTo(0.0, 250.0)

    // A conditional cache hit updates the cache.
    Thread.sleep(500) // Make sure t0 and t1 are distinct.
    val t1 = System.currentTimeMillis()
    val response2 = get(server.url("/a"))
    assertThat(response2.code).isEqualTo(HttpURLConnection.HTTP_OK)
    assertThat(response2.body.string()).isEqualTo("A")