// Entry 2: IPC$, type 3 (IPC), remark "Inter-Process Communication"
        System.arraycopy("IPC$".getBytes(StandardCharsets.US_ASCII), 0, data, 20, 4);
        data[34] = 0x03;
        data[35] = 0x00; // type = 3
        data[36] = 60;
        data[37] = 0;
        data[38] = 0;
        data[39] = 0; // remark offset

        // Remarks data

 *
 * <ol>
 *   <li>remove();
 *   <li>hasNext()
 *   <li>hasNext();
 *   <li>remove();
 *   <li>next();
 * </ol>
 *
 * <p>This particular order of operations may be unrealistic, and testing all 3^5 of them may be
 * thought of as overkill; however, it's difficult to determine which proper subset of this massive
 * set would be sufficient to expose any possible bug. Brute force is simpler.
 *

            (byte) 49, (byte) 41, (byte) 33, (byte) 25, (byte) 17, (byte) 9, (byte) 1, (byte) 58, (byte) 50, (byte) 42, (byte) 34,
            (byte) 26, (byte) 18, (byte) 10, (byte) 2, (byte) 59, (byte) 51, (byte) 43, (byte) 35, (byte) 62, (byte) 54, (byte) 46,
            (byte) 38, (byte) 30, (byte) 22, (byte) 14, (byte) 6, (byte) 61, (byte) 53, (byte) 45, (byte) 37, (byte) 29, (byte) 21,

   * <p>For example, if {@code rangeMap} had the entries {@code [1, 5] => "foo", (6, 8) => "bar",
   * (10, ∞) => "baz"} then {@code rangeMap.subRangeMap(Range.open(3, 12))} would return a range map
   * with the entries {@code (3, 5] => "foo", (6, 8) => "bar", (10, 12) => "baz"}.
   *
   * <p>The returned range map supports all optional operations that this range map supports, except
   * for {@code asMapOfRanges().iterator().remove()}.
   *

        String name2 = "DOMAIN          ";
        System.arraycopy(name2.getBytes("US-ASCII"), 0, src, srcIndex + 19, 16);
        src[srcIndex + 34] = 0x00; // hex code
        src[srcIndex + 35] = (byte) 0x84; // flags: group, active

        // Third name entry (18 bytes) - matching queryAddress
        String name3 = "TEST            ";
        System.arraycopy(name3.getBytes("US-ASCII"), 0, src, srcIndex + 37, 16);

Por ejemplo, el modelo anterior declara un “`object`” JSON (o `dict` en Python) como:

```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

...dado que `description` y `tax` son opcionales (con un valor por defecto de `None`), este “`object`” JSON también sería válido:

```JSON
{
    "name": "Foo",
    "price": 45.2
}
```

		//    * Listing an object with a trailing slash and '/' delimiter
		34: {
			IsTruncated: false,
			Objects:     []ObjectInfo{},
		},
		// ListObjectsResult-35 list with custom uncommon delimiter
		35: {
			IsTruncated: false,
			Objects: []ObjectInfo{
				{Name: "file1/receipt.json"},
			},
			Prefixes: []string{"file1/guidSplunk"},
		},

    assertFalse(rangeSet.encloses(Range.greaterThan(5)));

    RangeSet<Integer> expectedComplement =
        ImmutableRangeSet.<Integer>builder()
            .add(Range.lessThan(1))
            .add(Range.closedOpen(3, 5))
            .add(Range.greaterThan(8))
            .build();

    assertEquals(expectedComplement, rangeSet.complement());
  }

  public void testMultipleBoundedBelowRanges() {

///

#### 기본값이 있는 필드를 갖는 값의 데이터

하지만 모델의 필드가 기본값이 있어도 ID가 `bar`인 항목(items)처럼 데이터가 값을 갖는다면:

```Python hl_lines="3  5"
{
    "name": "Bar",
    "description": "The bartenders",
    "price": 62,
    "tax": 20.2
}
```

응답에 해당 값들이 포함됩니다.

#### 기본값과 동일한 값을 갖는 데이터

                'capabilities excluding version %s.' % ver)
          all_valid = False
        if ver < 3.5:
          print('WARNING: XLA does not support CUDA compute capabilities '
                'lower than 3.5. Disable XLA when running on older GPUs.')

    if all_valid:
      break

    # Reset and Retry