Estimation of Software Reliability by Sequential Testing with Simulated Annealing of Mean Field Approximation

Various problems of combinatorial optimization and permutation can be solved with neural network optimization. The problem of estimating the software reliability can be solved with the optimization of failed components to its minimum value. Various solutions of the problem of estimating the software reliability have been given. These solutions are exact and heuristic, but all the exact approaches are of considerable theoretical interest. In this paper, we propose the simulated annealing technique of mean field approximation for finding the possible minimum number of failed components in the sequential testing. These minimum numbers of failed components are depending upon the selection of time intervals or slots. The selection of time intervals or slots satisfies all the necessary constraints of the problem. The new energy function with the mean field approximation is also proposed. The constraint parameter for the annealing schedule is also dynamically defined that is changed with the selection of a time interval or slot on each iteration of the processing. The algorithm of the whole process shows that this approach can generate the optimal solution.