基于MARTE模型的系统可靠性预测  

MARTE Models Based System Reliability Prediction

作　　者：柴叶生 朱雪阳[2] 晏荣杰[2] 张广泉[1] 

机构地区：[1]苏州大学计算机科学与技术学院,苏州215000 [2]中国科学院软件研究所计算机科学国家重点实验室,北京100190

出　　处：《计算机科学》2015年第12期82-86,91,共6页Computer Science

基　　金：江苏省自然科学基金(BK2011281);苏州市应用基础研究计划(SYG201241)资助

摘　　要：系统的可靠性是系统的重要非功能属性之一。传统的可靠性分析在系统开发结束后进行,可能会发现由于系统开发早期的架构设计不合理而导致的问题,这时再修改系统架构并重做后继开发步骤,将会浪费大量人力和物力。如果能在开发的早期阶段,在系统模型层面进行分析并预测,则可以尽早地发现系统可靠性方面的问题并将其修复。UML是一种通用的、标准化的建模语言,MARTE是UML在嵌入式实时系统领域的扩展。提出了基于MARTE模型的系统可靠性预测方法,该方法考虑的MARTE模型包括用例图、活动图、部署图。先将MARTE模型转换为马尔可夫决策过程网络模型,再利用概率模型检测工具PRISM进行分析,得到系统可靠性的预测结果。实例研究表明,所提方法不仅能够预测系统可靠性的最大值和最小值,还能通过调整各个资源的可靠性值,考察其对系统可靠性的影响,为设计人员的进一步工作提供参考。System reliability is an important qualitative attribute of systems. System reliability analysis based on models may find problems and solve them at the early phase of development. UML profile for MARTE is an extension of UML in the domain of real-time and embedded systems. We presented a method for reliability prediction of MARTE models. The MARTE model considerd by the method includes a use case diagram,a deployment diagram and a set of activity diagrams. A MARTE model is transformed into a network of Markov decision process, which is then analyzed by the model checking tool PRISM. We obtained the estimation of system reliability by analyzing the resulting model. A case study demonstrates that, by analyzing models with various resource reliability, our method can further reveal the impact of the reliability of each resource on the system.

关 键 词：系统可靠性 UML MARTE模型 马尔可夫决策过程 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]