Abstract
Software reliability is estimated and predicted based on software reliability model and software failure data. As a new optimization method, swarm intelligence algorithm has been widely used in solving the parameter optimization of the model. WPA (Wolf Pack Algorithm) and PSO (Particle Swarm Optimization) are two typical swarm intelligence algorithms. WPA has a strong global optimization ability, fast convergence speed and various optimization strategies, but the algorithm is relatively complex. PSO algorithm has a simple structure and fast convergence speed, but it is easy to fall into premature, which leads to low accuracy of solution. Considering the advantages and disadvantages of the two algorithms, a hybrid method of WPA and PSO is proposed, and a fitness function is constructed on maximum likelihood estimation, then the parameters of software reliability model are estimated and predicted based on the hybrid algorithm (WPA-PSO). Five sets of data from industry are used to estimate the parameters of GO model and make predictions. The simulation results show that the hybrid algorithm has higher accuracy of parameter estimation, better optimization performance, better accuracy of prediction and algorithm stability than single algorithm, and show obvious advantages than the single algorithm in the case of limited data.
Highlights
Software reliability is a qualitative indicator for measuring software quality and has important research significance, so it is getting more and more attention from researchers
The Wolf Pack Algorithm (WPA) is a typical swarm intelligence algorithm, The associate editor coordinating the review of this manuscript and approving it for publication was Jagdish Chand Bansal
The results show that the estimation and prediction of the hybrid algorithm are better than the other two algorithms
Summary
Software reliability is a qualitative indicator for measuring software quality and has important research significance, so it is getting more and more attention from researchers. Researchers have put forward nearly a hundred software reliability models, such as GO model [1], MO model [2] and JM model [3], and so on. These models are nonlinear function models, and it is difficult to directly estimate their parameters. A new idea is to apply the intelligent optimization algorithm to the model parameter estimation. As a swarm intelligence optimization algorithm, WPA (Wolf Pack Algorithm) is proposed by Wu et al [4]. The WPA is a typical swarm intelligence algorithm, The associate editor coordinating the review of this manuscript and approving it for publication was Jagdish Chand Bansal
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