Prediction of quality software quality indicators with applied modifications of integrated gradiates methods

The article is devoted to modern software systems (SS) and improving their quality using machine learning methods, including the Integrated Gradients (IG) method. Key problems and limitation of IG use in real operating conditions of the SS, such as complexity of systems, correlation of variables and computing efficiency are considered. Ways to improve IG, including adaptive integration, spatial smoothing and use of weight factors, are proposed. Experimental results are described that confirm the effectiveness of the proposed modifications to improve the quality of the SS. Adaptive integration has achieved the best results (MAE 0.11), adaptability and interpretation.