Deriving Markov Chain Usage Model from UML Model

Constructing software usage model is basic for software reliability testing and software reliability evaluation. In recent years, how to derive Markov chain usage model from UML model has gained much attention. For large software system, the state space of Markov chain usage model using the existing methods is too large to describe, which is bad for generating test cases automatically and evaluating software reliability. For the above problems, a new method deriving a Markov chain usage model from UML model is proposed. The preconditions and postconditions of scenario are taken as the states of Markov chain usage model, and the performance and the performance probability of scenario are taken as the transition driver and transition probability. Compared with other methods, the state space of gained Markov chain usage model by proposed method is smaller and the constructing process is direct and automatic. Furthermore, the test cases can be generated easily by using the above method. In order to validate the validity of the UML model, the validity algorithm from UML model, which is extended by reliability evaluation to Markov chain model, is proposed too. Finally, the performance of the proposed method is verified by an example.