Modeling Mechanism and Review of Imperfect Debugging Reliability Model Related to the Total Number of Faults in Software

In the reliability research,the total number of software faults is crucial for allocating testing resources,assessing reliability changes,and determining optimal release times.However,there has been limited research from the perspective of total faults counts thus far.This study delves deeply into reliability growth models related to the total number of faults in software,particularly in environments that closely mimic real testing scenarios,including imperfect debugging.Initially,the study reviews the software reliability growth model(SRGM),outlining its main themes,essence,and technical content,and introduces analysis of total failures in software.It incorporates models that introduce new faults from the perspective of imperfect debugging,and establishes an imperfect debugging model to categorize the dynamics of total failures and cumulative detected failures under various conditions.Subsequently,from the perspectives of imperfect debugging and the introduction of new faults,a unified binary first-order imperfect debugging system of differential equations is developed to describe the software testing process.Solutions are derived for expressions of total failures and cumulative detected failures.The performance of these models is validated against multiple real-world computer engineering system faults datasets,analyzing their fit and predictive capabilities,thereby assessing the impact of total failures on reliability variations.The results indicate that the total number of failures significantly influences the reliability models and supports the growth and performance enhancement of reliability.Finally,this paper highlights forthcoming research challenges and pressing issues that need to be addressed.