assertEquals(0, new BigDecimal("0.000123").compareTo(BigDecimalConversionUtil.toBigDecimal(Double.valueOf(0.000123D))));
        assertEquals(0, new BigDecimal("0.0000123").compareTo(BigDecimalConversionUtil.toBigDecimal(Double.valueOf(0.0000123D))));
        assertEquals(0, new BigDecimal("0.00000123").compareTo(BigDecimalConversionUtil.toBigDecimal(Double.valueOf(0.00000123D))));

//	}
	MOVV	R25, R17	// 00198825
	MOVV	R1, R2		// 00011025
	MOVV	LO, R1		// 00000812
	MOVV	HI, R1		// 00000810
	MOVV	R1, LO		// 00200013
	MOVV	R1, HI		// 00200011


//	LMOVW rreg ',' rreg
//	{
//		outcode(int($1), &$2, 0, &$4);
//	}
	MOVW	R1, R2		// 00011004
	MOVW	LO, R1		// 00000812
	MOVW	HI, R1		// 00000810
	MOVW	R1, LO		// 00200013
	MOVW	R1, HI		// 00200011
	MOVWU	R14, R27	// 000ed83c001bd83e

		{+1, +1e0 - 0e0, "1.000000001"},
		{0, 1e9 - 1e0, "0.999999999"},
		{0, 1e9 - 1e3, "0.999999"},
		{0, 1e9 - 1e6, "0.999"},
		{0, 0e0, "0"},
		{0, 1e6 + 0e0, "0.001"},
		{0, 1e3 + 0e0, "0.000001"},
		{0, 1e0 + 0e0, "0.000000001"},
		{-1, -1e9 + 1e0, "-1.999999999"},
		{-1, -1e9 + 1e3, "-1.999999"},
		{-1, -1e9 + 1e6, "-1.999"},
		{-1, -0e0 + 0e0, "-1"},
		{-1, -1e6 + 0e0, "-1.001"},

        return Stream.of(Arguments.of(NtStatus.NT_STATUS_ACCESS_DENIED, NtStatus.NT_STATUS_ACCESS_DENIED),
                Arguments.of(NtStatus.NT_STATUS_SUCCESS, NtStatus.NT_STATUS_SUCCESS),
                Arguments.of(0x00001234, NtStatus.NT_STATUS_UNSUCCESSFUL));
    }

    @ParameterizedTest
    @MethodSource("intErrorCodes")
    @DisplayName("int ctor: sets message and NT status as expected")

     */

    /** The operation completed successfully */
    int NT_STATUS_SUCCESS = 0x00000000;
    /** The request is pending */
    int NT_STATUS_PENDING = 0x00000103;
    /** A notify change request is being completed and information is being returned */
    int NT_STATUS_NOTIFY_ENUM_DIR = 0x0000010C;
    /** The data was too large to fit into the specified buffer */

  // Load the saved model.
  const string saved_model_dir = tensorflow::GetDataDependencyFilepath(
      tensorflow::io::JoinPath("tensorflow", "cc", "saved_model", "testdata",
                               "half_plus_two", "00000123"));
  TF_SessionOptions* opt = TF_NewSessionOptions();
  TF_Buffer* run_options = TF_NewBufferFromString("", 0);
  TF_Buffer* metagraph = TF_NewBuffer();
  TF_Status* s = TF_NewStatus();

    assertThat(parse("http://[0:a:b:c:d:e:f:1]/").host).isEqualTo("0:a:b:c:d:e:f:1")
    assertThat(parse("http://[a:b:c:d:e:f:1:0]/").host).isEqualTo("a:b:c:d:e:f:1:0")
    assertThat(parse("http://[FF01:0:0:0:0:0:0:101]/").host).isEqualTo("ff01::101")
    assertThat(parse("http://[2001:db8::1]/").host).isEqualTo("2001:db8::1")
    assertThat(parse("http://[2001:db8:0:0:0:0:2:1]/").host).isEqualTo("2001:db8::2:1")

00000e0 67 65 34 f8 37 76 2d 76 5c 54 f3 95 65 49 c7 0f
00000f0 18 71 4b 7e 5b 6a d1 79 47 61 41 b0 4e 2a 74 45
0000100 43 58 12 b2 5a a5 c6 7d 68 55 88 d4 98 75 18 6d
0000110 08 d1 1f 8f 5a 9e 96 ee 45 cf a4 84 4e 4b e8 50
0000120 a7 13 d9 06 de 52 81 97 36 b2 d7 b8 fc 2b 5f 55
0000130 23 1f 32 59 cf 30 27 fb e2 8a b9 de 45 dd 63 9c
0000140 4b b5 8b 96 4c 7a 62 62 cc a1 a7 cf fa f1 fe dd
0000150 54 62 11 bf 36 78 b3 c7 b1 b5 f2 61 4d 4e dd 66

of // the padding. Sections 6.1 and 6.2 of [1] separate the outputs of the // SHA-3 and SHAKE functions by appending bitstrings to the message. // Using a little-endian bit-ordering convention, these are "01" for SHA-3 // and "1111" for SHAKE, or 00000010b and 00001111b, respectively. Then the // padding rule from section 5.1 is applied to pad the message to a multiple // of the rate, which involves adding a "1" bit, zero or more "0" bits, and // a final "1" bit. We merge the first "1" bit from the...