Application of LSTM-GRU combined model to calculate the reliability of software systems
Tamilla A. Bayramova, Tofig H. Kazimov · Procedia Computer Science · 2025
This study investigated the effectiveness of deep learning models in assessing the reliability of software systems and the application of recurrent neural network algorithms in reliability prediction. A hybrid model consisting of a combination of LSTM and GRU models is proposed to predict the reliability of software systems. Along with historical data collected during testing and implementation, several environmental factors covering the software life cycle and affecting its reliability, as well as the complexity of the software code, are taken as input. Based on these data, a new method for expert assessment of software reliability is proposed, and the calculated expert scores are taken as output. The proposed model is trained based on these values. This is a comprehensive approach to assessing the reliability of software systems.