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diff --git a/tests/validation_old/ReferenceCPP.cpp b/tests/validation_old/ReferenceCPP.cpp
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--- a/tests/validation_old/ReferenceCPP.cpp
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-/*
- * Copyright (c) 2017 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "ReferenceCPP.h"
-
-#include "TensorFactory.h"
-#include "TensorOperations.h"
-#include "TensorVisitors.h"
-
-#include "arm_compute/core/Coordinates.h"
-#include "arm_compute/core/Error.h"
-#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "utils/TypePrinter.h"
-
-#include "tests/validation_old/boost_wrapper.h"
-
-#include <algorithm>
-#include <functional>
-#include <memory>
-#include <numeric>
-#include <vector>
-
-using namespace arm_compute::test::validation::tensor_visitors;
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-// Harris corners
-void ReferenceCPP::harris_corners(RawTensor &src, RawTensor &Gx, RawTensor &Gy, const RawTensor &candidates, const RawTensor &non_maxima, float threshold, float min_dist, float sensitivity,
-                                  int32_t gradient_size, int32_t block_size, KeyPointArray &corners, BorderMode border_mode, uint8_t constant_border_value)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || (Gx.data_type() != DataType::S16 && Gx.data_type() != DataType::S32) || (Gy.data_type() != DataType::S16 && Gy.data_type() != DataType::S32)
-                         || candidates.data_type() != DataType::F32 || non_maxima.data_type() != DataType::F32);
-
-    Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<float>   c(candidates.shape(), candidates.data_type(), candidates.fixed_point_position(), const_cast<float *>(reinterpret_cast<const float *>(candidates.data())));  // NOLINT
-    Tensor<float>   nm(non_maxima.shape(), non_maxima.data_type(), non_maxima.fixed_point_position(), const_cast<float *>(reinterpret_cast<const float *>(non_maxima.data()))); // NOLINT
-
-    if(gradient_size == 7)
-    {
-        Tensor<int32_t> gx(Gx.shape(), Gx.data_type(), Gx.fixed_point_position(), reinterpret_cast<int32_t *>(Gx.data()));
-        Tensor<int32_t> gy(Gy.shape(), Gy.data_type(), Gy.fixed_point_position(), reinterpret_cast<int32_t *>(Gy.data()));
-        tensor_operations::harris_corners(s, gx, gy, c, nm, threshold, min_dist, sensitivity, gradient_size, block_size, corners, border_mode, constant_border_value);
-    }
-    else
-    {
-        Tensor<int16_t> gx(Gx.shape(), Gx.data_type(), Gx.fixed_point_position(), reinterpret_cast<int16_t *>(Gx.data()));
-        Tensor<int16_t> gy(Gy.shape(), Gy.data_type(), Gy.fixed_point_position(), reinterpret_cast<int16_t *>(Gy.data()));
-        tensor_operations::harris_corners(s, gx, gy, c, nm, threshold, min_dist, sensitivity, gradient_size, block_size, corners, border_mode, constant_border_value);
-    }
-}
-
-// Absolute difference
-void ReferenceCPP::absolute_difference(const RawTensor &src1, const RawTensor &src2, RawTensor &dst)
-{
-    const TensorVariant s1 = TensorFactory::get_tensor(src1);
-    const TensorVariant s2 = TensorFactory::get_tensor(src2);
-    TensorVariant       d  = TensorFactory::get_tensor(dst);
-    boost::apply_visitor(absolute_difference_visitor(), s1, s2, d);
-}
-
-// Integral image
-void ReferenceCPP::integral_image(const RawTensor &src, RawTensor &dst)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U32);
-    const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<uint32_t>      d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint32_t *>(dst.data()));
-    tensor_operations::integral_image(s, d);
-}
-
-// Accumulate
-void ReferenceCPP::accumulate(const RawTensor &src, RawTensor &dst)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::S16);
-    const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<int16_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data()));
-    tensor_operations::accumulate(s, d);
-}
-
-// Accumulate squared
-void ReferenceCPP::accumulate_squared(const RawTensor &src, RawTensor &dst, uint32_t shift)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::S16);
-    const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<int16_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<int16_t *>(dst.data()));
-    tensor_operations::accumulate_squared(s, d, shift);
-}
-
-// Accumulate weighted
-void ReferenceCPP::accumulate_weighted(const RawTensor &src, RawTensor &dst, float alpha)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
-    const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
-    tensor_operations::accumulate_weighted(s, d, alpha);
-}
-
-// Non linear filter
-void ReferenceCPP::non_linear_filter(const RawTensor &src, RawTensor &dst, NonLinearFilterFunction function, unsigned int mask_size,
-                                     MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
-    const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
-    tensor_operations::non_linear_filter(s, d, function, mask_size, pattern, mask, border_mode, constant_border_value);
-}
-
-// Threshold
-void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)
-{
-    ARM_COMPUTE_ERROR_ON(src.data_type() != DataType::U8 || dst.data_type() != DataType::U8);
-    const Tensor<uint8_t> s(src.shape(), src.data_type(), src.fixed_point_position(), reinterpret_cast<const uint8_t *>(src.data()));
-    Tensor<uint8_t>       d(dst.shape(), dst.data_type(), dst.fixed_point_position(), reinterpret_cast<uint8_t *>(dst.data()));
-    tensor_operations::threshold(s, d, threshold, false_value, true_value, type, upper);
-}
-
-// ROI Pooling Layer
-void ReferenceCPP::roi_pooling_layer(const RawTensor &src, RawTensor &dst, const std::vector<ROI> &rois, const ROIPoolingLayerInfo &pool_info)
-{
-    const TensorVariant s = TensorFactory::get_tensor(src);
-    TensorVariant       d = TensorFactory::get_tensor(dst);
-    boost::apply_visitor(tensor_visitors::roi_pooling_layer_visitor(s, rois, pool_info), d);
-}
-
-} // namespace validation
-} // namespace test
-} // namespace arm_compute