During October 2025, Dani García-Peña focused on enhancing the reliability of model evaluation in the Artelnics/opennn repository by developing comprehensive unit tests for dataset handling and CrossEntropyError computations. Working primarily in C++ and leveraging skills in data preprocessing and error metrics, Dani refactored and expanded the existing test suite to cover a broader range of data types, correlations, and error calculations. This work improved the robustness and correctness of the codebase, strengthened continuous integration signals, and reduced production risk. By linking changes to specific commits, Dani also improved traceability, making future code reviews and potential rollbacks more efficient.