diff --git a/Start_Windows/neuralNetworkTests.c b/Start_Windows/neuralNetworkTests.c
index 9e4ed7b..37b048d 100644
--- a/Start_Windows/neuralNetworkTests.c
+++ b/Start_Windows/neuralNetworkTests.c
@@ -23,51 +23,6 @@
 // 2) Stellen Sie sicher, dass alle Unittests erfolgreich durchlaufen.
 // make neuralNetworkTests && ./runNeuralNetworkTests
 
-// static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
-// {
-//     // First Draft
-//
-//     // 1. Datei im binären Schreibmodus öffnen
-//     FILE *file = fopen(path, "wb");
-//     if (file == NULL) {
-//         perror("Fehler beim Öffnen der Datei");
-//         return;
-//     }
-//
-//     // 2. Den Identifikations-Tag schreiben
-//     const char *fileTag = "__info2_neural_network_file_format__";
-//     fwrite(fileTag, sizeof(char), strlen(fileTag), file);
-//
-//     // 3. Die Anzahl der Schichten schreiben
-//     fwrite(&nn.numberOfLayers, sizeof(int), 1, file);
-//
-//     // 4. Schleife über alle Schichten, um deren Daten zu schreiben
-//     for (int i = 0; i < nn.numberOfLayers; i++) {
-//         Layer currentLayer = nn.layers[i];
-//
-//         // 4a. Daten der Gewichts-Matrix (weights) schreiben
-//         Matrix weights = currentLayer.weights;
-//         int weightElements = weights.rows * weights.cols;
-//
-//         // Schreibe Dimensionen (Zeilen, Spalten)
-//         fwrite(&weights.rows, sizeof(int), 1, file);
-//         fwrite(&weights.cols, sizeof(int), 1, file);
-//         // Schreibe den Daten-Buffer (die eigentlichen Zahlen)
-//         fwrite(weights.buffer, sizeof(MatrixType), weightElements, file);
-//
-//         // 4b. Daten der Bias-Matrix (biases) schreiben
-//         Matrix biases = currentLayer.biases;
-//         int biasElements = biases.rows * biases.cols;
-//
-//         // Schreibe Dimensionen (Zeilen, Spalten)
-//         fwrite(&biases.rows, sizeof(int), 1, file);
-//         fwrite(&biases.cols, sizeof(int), 1, file);
-//         // Schreibe den Daten-Buffer
-//         fwrite(biases.buffer, sizeof(MatrixType), biasElements, file);
-//     }
-//     // 5. Datei schließen
-//     fclose(file);
-// }
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {