面向随机模型检验的模型抽象技术

随机模型检验是经典模型检验理论的延伸和推广,由于其结合了经典模型检验算法和线性方程组求解或线性规划算法等,并且运算处理的是关于状态的概率向量而非经典模型检验中的位向量,所以状态爆炸问题在随机模型检验中更为严重.抽象作为缓解状态空间爆炸问题的重要技术之一,已经开始被应用到随机模型检验领域并取得了一定的进展.以面向随机模型检验的模型抽象技术为研究对象,首先给出了模型抽象技术的问题描述,然后按抽象模型构造技术分类归纳了其研究方向及目前的研究进展,最后对比了目前的模型抽象技术及其关系,总结出其还未能给出模型抽象问题的满意答案,并指出了有效解决模型抽象问题未来的研究方向.

Model Abstraction for Stochastic Model Checking

Stochastic model checking is a recent extension and generalization of the classical model checking. Stochastic model checking combines the classical model checking algorithms and linear equation solving or linear programming algorithms, moreover, it processes the probability vector instead of the bit vector. Consequently, the state explosion problem is more severe in stochastic model checking than classical model checking. Abstraction is an important means to tackle the state explosion problem, and it has made some progress in applying to the field of stochastic models testing. This study focus on model abstraction for stochastic model checking. First, the problem of model abstraction is formally presented. Then, the advances in the research area are classified and summarized according to the construction technology of abstraction model. At last, the various abstraction technologies are compared in regard to the effectiveness of solving the model abstraction problem, and the future research topics for improvement in solving the model abstraction problem are pointed out.