diff --git a/tests/fann_test.cpp b/tests/fann_test.cpp
index 7ba9fec8..42d2da41 100644
--- a/tests/fann_test.cpp
+++ b/tests/fann_test.cpp
@@ -61,7 +61,7 @@ void FannTest::AssertWeights(neural_net &net, fann_type min, fann_type max, fann
 
 TEST_F(FannTest, CreateStandardThreeLayers) {
     neural_net net(LAYER, 3, 2, 3, 4);
-    AssertCreateAndCopy(net, 3, (unsigned int[]) {2, 3, 4}, 11, 25);
+    AssertCreateAndCopy(net, 3, (const unsigned int[]) {2, 3, 4}, 11, 25);
 }
 
 TEST_F(FannTest, CreateStandardThreeLayersUsingCreateMethod) {
@@ -90,12 +90,12 @@ TEST_F(FannTest, CreateStandardFourLayersVector) {
 
 TEST_F(FannTest, CreateSparseFourLayers) {
     neural_net net(0.5, 4, 2, 3, 4, 5);
-    AssertCreateAndCopy(net, 4, (unsigned int[]){2, 3, 4, 5}, 17, 31);
+    AssertCreateAndCopy(net, 4, (const unsigned int[]){2, 3, 4, 5}, 17, 31);
 }
 
 TEST_F(FannTest, CreateSparseFourLayersUsingCreateMethod) {
     ASSERT_TRUE(net.create_sparse(0.5f, 4, 2, 3, 4, 5));
-    AssertCreateAndCopy(net, 4, (unsigned int[]){2, 3, 4, 5}, 17, 31);
+    AssertCreateAndCopy(net, 4, (const unsigned int[]){2, 3, 4, 5}, 17, 31);
 }
 
 TEST_F(FannTest, CreateSparseArrayFourLayers) {
@@ -118,13 +118,13 @@ TEST_F(FannTest, CreateSparseArrayWithMinimalConnectivity) {
 
 TEST_F(FannTest, CreateShortcutFourLayers) {
     neural_net net(SHORTCUT, 4, 2, 3, 4, 5);
-    AssertCreateAndCopy(net, 4, (unsigned int[]){2, 3, 4, 5}, 15, 83);
+    AssertCreateAndCopy(net, 4, (const unsigned int[]){2, 3, 4, 5}, 15, 83);
     EXPECT_EQ(SHORTCUT, net.get_network_type());
 }
 
 TEST_F(FannTest, CreateShortcutFourLayersUsingCreateMethod) {
     ASSERT_TRUE(net.create_shortcut(4, 2, 3, 4, 5));
-    AssertCreateAndCopy(net, 4, (unsigned int[]){2, 3, 4, 5}, 15, 83);
+    AssertCreateAndCopy(net, 4, (const unsigned int[]){2, 3, 4, 5}, 15, 83);
     EXPECT_EQ(SHORTCUT, net.get_network_type());
 }
 
@@ -148,7 +148,7 @@ TEST_F(FannTest, CreateFromFile) {
     ASSERT_TRUE(netToBeSaved.save("tmpfile"));
 
     neural_net netToBeLoaded("tmpfile");
-    AssertCreateAndCopy(netToBeLoaded, 3, (unsigned int[]){2, 3, 4}, 11, 25);
+    AssertCreateAndCopy(netToBeLoaded, 3, (const unsigned int[]){2, 3, 4}, 11, 25);
 }
 
 TEST_F(FannTest, CreateFromFileUsingCreateMethod) {
@@ -158,7 +158,7 @@ TEST_F(FannTest, CreateFromFileUsingCreateMethod) {
 
     ASSERT_TRUE(net.create_from_file("tmpfile"));
 
-    AssertCreateAndCopy(net, 3, (unsigned int[]){2, 3, 4}, 11, 25);
+    AssertCreateAndCopy(net, 3, (const unsigned int[]){2, 3, 4}, 11, 25);
 }
 
 TEST_F(FannTest, RandomizeWeights) {
diff --git a/tests/fann_test_train.cpp b/tests/fann_test_train.cpp
index bd7c0edd..c68b334a 100644
--- a/tests/fann_test_train.cpp
+++ b/tests/fann_test_train.cpp
@@ -25,10 +25,10 @@ TEST_F(FannTestTrain, TrainSimpleIncrementalXor) {
     neural_net net(LAYER, 3, 2, 3, 1);
 
     for(int i = 0; i < 100000; i++) {
-        net.train((fann_type[]) {0.0, 0.0}, (fann_type[]) {0.0});
-        net.train((fann_type[]) {1.0, 0.0}, (fann_type[]) {1.0});
-        net.train((fann_type[]) {0.0, 1.0}, (fann_type[]) {1.0});
-        net.train((fann_type[]) {1.0, 1.0}, (fann_type[]) {0.0});
+        net.train((fann_type*) (const fann_type[]) {0.0, 0.0}, (fann_type*) (const fann_type[]) {0.0});
+        net.train((fann_type*) (const fann_type[]) {1.0, 0.0}, (fann_type*) (const fann_type[]) {1.0});
+        net.train((fann_type*) (const fann_type[]) {0.0, 1.0}, (fann_type*) (const fann_type[]) {1.0});
+        net.train((fann_type*) (const fann_type[]) {1.0, 1.0}, (fann_type*) (const fann_type[]) {0.0});
     }
 
     EXPECT_LT(net.get_MSE(), 0.01);