Software Reliability Growth Model with Rate of Change in Application Characteristics

Background: There has been continuous advancement in technologies for the past few decades by incorporating new features in accordance with the market demand. The evolution of software projects/applications has an intricated debugging process by generating numerous faults in it. Objectives: In this study, an attempt is made to develop a software reliability growth model (SRGM) taking into account the software project/application’s characteristics, such as complexity of code and testing environment. The simulation is based on previous fault data in order to foresee the future latent faults occurring in the system for a given time frame. This model not only forecasts the number of faults but is an extended version of Kapur and Garg’s error removal phenomenon model incorporating factors that might have an influence on the model. Methods: The performance of the model is validated using three data sets and finally compared with extant models, namely GO model and Yamada model, to assess the proposed model’s efficiency. Results: The parameter estimations were significant, and the proposed model performed better in comparison to the other two models. Conclusion: The proposed model is a contribution to the studies on the reliability of the project and can be extended in the future by generalizing the results over various datasets and models.