diff --git a/Applications/Resnet/jni/main.cpp b/Applications/Resnet/jni/main.cpp
index 45eb0e95e0..7a4f17de90 100644
--- a/Applications/Resnet/jni/main.cpp
+++ b/Applications/Resnet/jni/main.cpp
@@ -18,6 +18,10 @@
 #include <sstream>
 #include <vector>
 
+#if defined(ENABLE_TEST)
+#include <gtest/gtest.h>
+#endif
+
 #include <layer.h>
 #include <model.h>
 #include <optimizer.h>
@@ -29,6 +33,10 @@ using ModelHandle = std::unique_ptr<ml::train::Model>;
 
 using UserDataType = std::unique_ptr<nntrainer::resnet::DataLoader>;
 
+/** cache loss values post training for test */
+float training_loss = 0.0;
+float validation_loss = 0.0;
+
 /**
  * @brief make "key=value" from key and value
  *
@@ -210,6 +218,13 @@ int validData_cb(float **input, float **label, bool *last, void *user_data) {
   return 0;
 }
 
+#if defined(ENABLE_TEST)
+TEST(Resnet_Training, verify_accuracy) {
+  EXPECT_FLOAT_EQ(training_loss, 4.389328);
+  EXPECT_FLOAT_EQ(validation_loss, 11.611803);
+}
+#endif
+
 /// @todo maybe make num_class also a parameter
 void createAndRun(unsigned int epochs, unsigned int batch_size,
                   UserDataType &train_user_data,
@@ -243,6 +258,10 @@ void createAndRun(unsigned int epochs, unsigned int batch_size,
                     std::move(dataset_valid));
 
   model->train();
+#if defined(ENABLE_TEST)
+  training_loss = model->getTrainingLoss();
+  validation_loss = model->getValidationLoss();
+#endif
 }
 
 std::array<UserDataType, 2>
@@ -327,5 +346,21 @@ int main(int argc, char *argv[]) {
   std::cout << "finished computation at " << std::ctime(&end_time)
             << "elapsed time: " << elapsed_seconds.count() << "s\n";
 
-  return 0;
+  int status = 0;
+#if defined(ENABLE_TEST)
+  try {
+    testing::InitGoogleTest(&argc, argv);
+  } catch (...) {
+    std::cerr << "Error duing InitGoogleTest" << std::endl;
+    return 0;
+  }
+
+  try {
+    status = RUN_ALL_TESTS();
+  } catch (...) {
+    std::cerr << "Error duing RUN_ALL_TSETS()" << std::endl;
+  }
+#endif
+
+  return status;
 }
diff --git a/Applications/Resnet/jni/meson.build b/Applications/Resnet/jni/meson.build
index ebeb72fd75..b950d2a27d 100644
--- a/Applications/Resnet/jni/meson.build
+++ b/Applications/Resnet/jni/meson.build
@@ -3,10 +3,20 @@ resnet_sources = [
   'cifar_dataloader.cpp'
 ]
 
+resnet_dependencies = [app_utils_dep,
+  iniparser_dep,
+  nntrainer_dep,
+  nntrainer_ccapi_dep
+]
+
+if get_option('enable-test')
+  resnet_dependencies += [gtest_dep]
+endif
+
 e = executable('nntrainer_resnet18',
   resnet_sources,
   include_directories: '.',
-  dependencies: [app_utils_dep, iniparser_dep, nntrainer_dep, nntrainer_ccapi_dep],
+  dependencies: resnet_dependencies,
   install: get_option('install-app'),
   install_dir: application_install_dir
 )
@@ -14,6 +24,6 @@ e = executable('nntrainer_resnet18',
 
 if get_option('enable-long-test')
   testenv = environment()
-  testenv.set('OPENBLAS_NUM_THREADS', 1)
-  test('app_resnet18', e, args: ['fake', '1', '512'], env: testenv, timeout: 300)
+  testenv.set('OPENBLAS_NUM_THREADS', '4')
+  test('app_resnet18', e, args: ['fake', '1', '128', '1'], env: testenv, timeout: 300)
 endif
diff --git a/nntrainer/tensor/tensor.cpp b/nntrainer/tensor/tensor.cpp
index 38062bd66b..f2de892e6f 100644
--- a/nntrainer/tensor/tensor.cpp
+++ b/nntrainer/tensor/tensor.cpp
@@ -740,9 +740,9 @@ Tensor Tensor::sum(const std::vector<unsigned int> &axes, float alpha) const {
   return sum(axes, ret, alpha);
 }
 
-void Tensor::merge_axis(unsigned int axis1, unsigned int axis2) {
+void Tensor::mergeAxis(unsigned int axis1, unsigned int axis2) {
   if (axis2 != axis1 + 1)
-    throw std::invalid_argument("Axis to be merged must be continuous.");
+    throw std::invalid_argument("axis2 must be axis1 + 1 for merging.");
 
   dim.setTensorDim(axis2, dim.getTensorDim(axis1) * dim.getTensorDim(axis2));
   dim.setTensorDim(axis1, 1);
@@ -761,7 +761,7 @@ Tensor &Tensor::sum(const std::vector<unsigned int> &axes, Tensor &output,
     std::vector<unsigned int> new_axes = {axes[0]};
     for (unsigned int i = 1; i < axes.size(); ++i) {
       if (axes[i] == axes[i - 1] + 1) {
-        new_reshaped.merge_axis(axes[i - 1], axes[i]);
+        new_reshaped.mergeAxis(axes[i - 1], axes[i]);
         new_axes.back() = axes[i];
       } else {
         new_axes.push_back(axes[i]);
diff --git a/nntrainer/tensor/tensor.h b/nntrainer/tensor/tensor.h
index b388eb7425..cd56f9ab75 100644
--- a/nntrainer/tensor/tensor.h
+++ b/nntrainer/tensor/tensor.h
@@ -1127,7 +1127,7 @@ class Tensor {
    * @param axis1 first axis to merge
    * @param axis2 second axis to merge
    */
-  void merge_axis(unsigned int axis1, unsigned int axis2);
+  void mergeAxis(unsigned int axis1, unsigned int axis2);
 }; // namespace nntrainer
 
 /**