// directio.AlignSize is defined as 0 in MacOS causing divide by 0 error.
const DirectioAlignSize = 4096

// CopyAligned - copies from reader to writer using the aligned input
// buffer, it is expected that input buffer is page aligned to
// 4K page boundaries. Without passing aligned buffer may cause
// this function to return error.
//

       * more information, see the comments in that class.
       *
       * We already know that that's how it behaves, and subclasses of Converter can't change that
       * behavior. So there's no sense in making all subclass authors exclude the method from any
       * NullPointerTester tests that they have.
       */
      ignoredMembers.add(Converter.class.getMethod("apply", Object.class));

      // originally was 2 * Math.log(...), making it try more times to avoid flakiness issues
      int maxCount = (int) (4 * Math.log(2 * keyBits * hashBits) + 1);
      while (same != 0xffffffff || diff != 0xffffffff) {
        int key1 = rand.nextInt();
        // flip input bit for key2
        int key2 = key1 ^ (1 << i);
        // get hashes
        int hash1 = function.hashInt(key1).asInt();

		delete(sys.metadataMap, bucket)
		globalBucketMonitor.DeleteBucket(bucket)
	}
}

// Set - sets a new metadata in-memory.
// Only a shallow copy is saved and fields with references
// cannot be modified without causing a race condition,
// so they should be replaced atomically and not appended to, etc.
// Data is not persisted to disk.
func (sys *BucketMetadataSys) Set(bucket string, meta BucketMetadata) {
	if !isMinioMetaBucketName(bucket) {

        // This should not throw exception, just do nothing
        try {
            WebApiUtil.setObject("testKey", "testValue");
        } catch (Exception e) {
            fail("setObject should handle missing request gracefully: " + e.getMessage());
        }
    }

    @Test
    public void test_setObject_withNullName() {
        // Test setObject with null name
        try {

                     TF_Status* status) {
  using tensorflow::NodeDef;
  using tensorflow::OpRegistrationData;
  using tensorflow::Tensor;
  using tensorflow::shape_inference::DimensionHandle;
  using tensorflow::shape_inference::InferenceContext;
  using tensorflow::shape_inference::ShapeAndType;
  using tensorflow::shape_inference::ShapeHandle;

  const int num_inputs = input_shapes->num_items;

        }
        getAvailableClient().streamGenerateAnswer(userMessage, documents, history, callback);
    }

    /**
     * Generates a response asking user for clarification.
     *
     * @param userMessage the user's message
     * @param history the conversation history
     * @param callback the streaming callback
     * @throws LlmException if LLM is not available

            IllegalArgumentException.class, () -> checkArgument(false, "A %s C", (Object) null));
    assertThat(e).hasMessageThat().isEqualTo("A null C");
  }

  @J2ktIncompatible // TODO(b/319404022): Allow passing null array as varargs
  public void testCheckArgument_singleNullArray_failure() {
    IllegalArgumentException e =
        assertThrows(

            IllegalArgumentException.class, () -> checkArgument(false, "A %s C", (Object) null));
    assertThat(e).hasMessageThat().isEqualTo("A null C");
  }

  @J2ktIncompatible // TODO(b/319404022): Allow passing null array as varargs
  public void testCheckArgument_singleNullArray_failure() {
    IllegalArgumentException e =
        assertThrows(

}

func errUnsupportedCast(fromType, toType string) error {
	return fmt.Errorf("Cannot cast from %v to %v", fromType, toType)
}

func errCastFailure(msg string) error {
	return fmt.Errorf("Error casting: %s", msg)
}

// Allowed cast types
const (
	castBool      = "BOOL"
	castInt       = "INT"
	castInteger   = "INTEGER"
	castString    = "STRING"
	castFloat     = "FLOAT"
	castDecimal   = "DECIMAL"