/**
     * Gets the pointer/offset to the string data.
     *
     * @return the pointer to the string data
     */
    public int getPointer() {
        return this.pointer;
    }

    /**
     * Validates the provided string against this structure's metadata.
     * Checks that the string length matches the expected length and that
     * null strings have a zero pointer.
     *
     * @param string the string to validate

/*
 * Copyright 2012-2025 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

/*
 * Copyright (C) 2011 The Guava Authors
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

    void testConstructorAndGetValue() {
        // Test that the constructor correctly initializes the value
        long expectedValue = 123456789012345L;
        NdrHyper ndrHyper = new NdrHyper(expectedValue);
        assertEquals(expectedValue, ndrHyper.value, "Constructor should set the correct value.");
    }

    @Test
    void testEncode() throws NdrException {
        // Test the encode method
        long testValue = 987654321098765L;

@REM Licensed to the Apache Software Foundation (ASF) under one
@REM or more contributor license agreements.  See the NOTICE file
@REM distributed with this work for additional information
@REM regarding copyright ownership.  The ASF licenses this file
@REM to you under the Apache License, Version 2.0 (the
@REM "License"); you may not use this file except in compliance
@REM with the License.  You may obtain a copy of the License at
@REM

/*
 * Copyright 2012-2025 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

/*
 * Copyright 2012-2025 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

/*
 * Copyright 2012-2025 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

#
#  Licensed to the Apache Software Foundation (ASF) under one or more
#  contributor license agreements.  See the NOTICE file distributed with
#  this work for additional information regarding copyright ownership.
#  The ASF licenses this file to You under the Apache License, Version 2.0
#  (the "License"); you may not use this file except in compliance with
#  the License.  You may obtain a copy of the License at
#
#       http://www.apache.org/licenses/LICENSE-2.0

   * values (i.e. it is the square root of the mean of the squares of the vertical distances between
   * the data points and the best fit line). For this fit, this error is a fraction {@code sqrt(1 -
   * R*R)} of the population standard deviation of {@code y}, where {@code R} is the Pearson's
   * correlation coefficient (as given by {@link #pearsonsCorrelationCoefficient()}).
   *