Abstract
The implemented approach is powerful method for estimating reliability of the software parameters growing SRGM by utilizing an Algorithm which is known as RGA. The full form of RGA is Real-valued Genetic Algorithm. Parameters required for current SRGM, if we take an illustration, the Failures average number or identification rate of the failure utilizing the techniques which are numerical, estimation of the maximum probability or estimation of minimum square.RGA means the free form of SRGM parameter estimation limitations. Instead of these, this can be much adapted for optimizing domain continuously compared to the algorithm of the binary genetic. The operators of GA which is 2 real valued crossovers& mutation of non-uniform interfaced for enhancing SRGM parameters estimation execution and accuracy enhancement. I led tests over eight datasets which are real valued to contrast implemented scheme & techniques of the numerical & another generic algorithm which are typical. The results describes that in estimation of SRGM parameters, the RGA is the most powerful compared to the others. So that we can trust the RGA which is the right solution for getting the efficient software quality with estimation of reliable accuracy.
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