* @return The data class.
     */
    public Class<?> getDataClass() {
        return dataClass;
    }

    /**
     * Sets the data class.
     * @param dataClass The data class to set.
     */
    public void setDataClass(final Class<?> dataClass) {
        this.dataClass = dataClass;
    }

    }

    /**
     * Returns the dataClass.
     *
     * @return the dataClass
     */
    public Class<?> getDataClass() {
        return dataClass;
    }

    /**
     * Sets the dataClass.
     *
     * @param dataClass the dataClass to set
     */
    public void setDataClass(final Class<?> dataClass) {
        this.dataClass = dataClass;
    }

    /**

                final int dataLen = SMBUtil.readInt2(buffer, ncpos + 2);

                // Validate context data length
                if (dataLen < 0 || dataLen > 1024) { // 1KB max per context
                    throw new SMBProtocolDecodingException(
                            "Invalid negotiate context data length: " + dataLen + " at position " + i + " (must be 0-1024)");
                }

    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);

    assertThat(manyValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStatsAccumulator accumulator =

        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);
    assertThat(manyValuesAccumulatorByAddAllStatsAccumulator.mean())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);
    // For datasets of many double values created from an iterable, we test many combinations of
    // finite and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      StatsAccumulator accumulator = new StatsAccumulator();

            json_schema_extra=json_schema_extra,
            **extra,
        )


@dataclass(frozen=True)
class Depends:
    dependency: Optional[Callable[..., Any]] = None
    use_cache: bool = True
    scope: Union[Literal["function", "request"], None] = None


@dataclass(frozen=True)
class Security(Depends):

        final Object obj = xpathTransformer.getData(accessResultDataImpl);
        assertNull(obj);
    }

    public void test_dataClass() {
        assertNull(xpathTransformer.dataClass);
        assertEquals(Map.class, xpathMapTransformer.dataClass);
    }

    public void test_getData_dataMap() throws Exception {
        final String value = "<?xml version=\"1.0\"?>\n"//
                + "<doc>\n"//