¹Department of IT, GITAM University, Visakhapatnam, Andhra Pradesh, India.
²Department of CSE, School of Computing, GRIET, Hyderabad, Telangana, India.

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Abstract—Software reliability engineering has recently turned out to be an interesting research topic in the field of software engineering. For the purpose of reliability calculation of software, various software reliability models have been designed based on the application of software in particular fields. The ability of the particular model in estimating the failure rate, reliability, and cost of the software are the major requirement in reliability modeling since any sort of failure or fault in the software can make the entire system unreliable to perform the desired operation. This paper proposes an efficient software reliability growth model (SRGM) model selection for estimating the reliability of the software. The reliability model selection criteria are generally based on the improved computational time and better failure rates. The selection of the model is done by utilizing optimization techniques. Here we have used modified cuckoo search optimization and modified ABC in order to find the effectiveness of the reliability model. Using these optimization algorithms, we evaluate various measures of the reliability models and are compared with that of other models. Here two different optimization approaches are used since we can efficiently find the best model using these algorithms.

Index Terms—Modified cuckoo search algorithm, modified artificial bee colony optimization, genetic algorithm, software reliability modeling, software reliability growth model, optimization techniques.

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Cite: Mallikharjuna Rao K., K. Anuradha, "An Efficient Method for Enhancing Reliability and Selection of Software Reliability Growth Model through Optimization Techniques," Journal of Software vol. 12, no. 1, pp. 1-18, 2017.