*
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**

          Assert.assertEquals(0.50d, prob, epsilon);
        }
      }
    }
  }

  /**
   * Checks that a Hasher returns the same HashCode when given the same input, and also that the
   * collision rate looks sane.
   */
  static void assertInvariants(HashFunction hashFunction) {
    int objects = 100;
    Set<HashCode> hashcodes = Sets.newHashSetWithExpectedSize(objects);
    Random random = new Random(314159);

          Assert.assertEquals(0.50d, prob, epsilon);
        }
      }
    }
  }

  /**
   * Checks that a Hasher returns the same HashCode when given the same input, and also that the
   * collision rate looks sane.
   */
  static void assertInvariants(HashFunction hashFunction) {
    int objects = 100;
    Set<HashCode> hashcodes = Sets.newHashSetWithExpectedSize(objects);
    Random random = new Random(314159);

   *
   * <p>See http://en.wikipedia.org/wiki/Bloom_filter#Probability_of_false_positives for the
   * formula.
   *
   * @param n expected insertions (must be positive)
   * @param p false positive rate (must be 0 < p < 1)
   */
  @VisibleForTesting
  static long optimalNumOfBits(long n, double p) {
    if (p == 0) {
      p = Double.MIN_VALUE;
    }

   * to hang (possibly too quickly, but too-quick failures should be very unlikely, given that we
   * used to bail after 20ms during the expected-successful tests, and there we saw a failure rate
   * of ~1/5000, meaning that the other thread's get() call nearly always completes within 20ms if
   * it's going to complete at all).
   *

   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**

            final Date date = toDate(str, format);
            if (date != null) {
                return date;
            }
        }
        final Date date = toDate(str, locale);
        if (date != null) {
            return date;
        }
        final Time time = toSqlTimeJdbcEscape(str);
        if (time != null) {
            return new Date(time.getTime());
        }

     * @throws Exception
     */
    @Test
    public void testGetAsObjectAndGetAsString() throws Exception {
        final SqlDateConverter converter = new SqlDateConverter("yyyy/MM/dd");
        final java.sql.Date result = (java.sql.Date) converter.getAsObject("2008/01/16");
        System.out.println(result);
        assertThat(converter.getAsString(result), is("2008/01/16"));
    }

    /**
     * @throws Exception
     */
    @Test

    public static final String DATE_FORMAT_ISO_8601_BASIC = "yyyyMMdd'T'HHmmss.SSSZ";

    public static final String DATE_FORMAT_ISO_8601_EXTEND = "yyyy-MM-dd'T'HH:mm:ss.SSSZ";

    public static final String DATE_FORMAT_ISO_8601_EXTEND_UTC = "yyyy-MM-dd'T'HH:mm:ss.SSS'Z'";

    public static final String DATE_FORMAT_DIGIT_ONLY = "yyyyMMddHHmmss";

    protected CoreLibConstants() {
    }

        assertEquals(777, DocumentUtil.getValue(doc, "key9", Integer.class));
    }

    public void test_date() {
        Map<String, Object> doc = new HashMap<>();

        Date expected4 = new Date();
        doc.put("key4", expected4);
        assertEquals(expected4, DocumentUtil.getValue(doc, "key4", Date.class));
    }

    public void test_long() {
        Map<String, Object> doc = new HashMap<>();