摘要
软件可靠性建模是一个重要的研究领域,现有的软件可靠性模型基本上是非线性函数模型,估计这些模型的参数比较困难。粒子群优化是一类适合求解非线性优化问题的随机优化方法,提出一种基于粒子群优化的软件可靠性模型估计参数方法,该方法的关键是构造合适的适应函数。用该方法分别估计了5个实际软件系统的指数软件可靠性模型以及对数泊松执行时间模型,实验结果表明:该方法参数估计的精度高,对模型的适应性强。
It is an important research field that models software reliability.Presented software reliability models are almost nonlinear function models,so it is difficult to estimate their parameters.Particle Swarm Optimizers are valuable stochastic optimization methods for various solving nonlinear optimization problems.A method of estimating parameters of software reliability models based on Particle Swarm Optimization is proposed in this paper.The key of this method is to construct fitness function for estimated software reliability models.Parameters of exponential software reliability growth model and logarithmic Poisson execution model of five software systems are estimated using proposed method respectively.The experimental results show that estimation precise of proposed method is high.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第11期47-49,共3页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.10672136)
关键词
软件可靠性模型
粒子群算法
参数估计
software reliability model
Particle Swarm Optimization （PSO）
parameter estimation
