A hybrid method for parameter estimation of software reliability growth model using Modified Genetic Swarm Optimization with the aid of logistic exponential testing effort function

The modern world is highly engaged with software systems. Determining the quality of a software system is a challenging task. Software reliability plays a vital role in the quality estimation of a software system and highly helped in achieving high-quality software. This paper proposes a hybrid method for estimating the parameters of Software Reliability Growth Model (SRGM) using Modified Genetic Swarm Optimization (MGSO) with the combination of logistic-exponential Testing Effort Function (TEF). Parameter estimation of SRGM is highly helped in reliability prediction which helps in determination of Software quality. Once the parameters are estimated, the parameters are optimized using MGSO. The proposed method implemented on working platform of JAVA and the effectiveness of proposed method estimated by comparing with existing methods.