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Early Stage Software Reliability Estimation with Stochastic Reward Nets
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作者 赵靖 刘宏伟 +1 位作者 崔刚 杨孝宗 《Journal of Donghua University(English Edition)》 EI CAS 2005年第3期33-36,共4页
This paper presents software reliability modeling issues at the early stage of a software development for fault tolerant software management system. Based on Stochastic Reward Nets, an effective model of hierarchical ... This paper presents software reliability modeling issues at the early stage of a software development for fault tolerant software management system. Based on Stochastic Reward Nets, an effective model of hierarchical view for a fault tolerant software management system is put forward, and an approach that consists of system transient performance analysis is adopted. A quantitative approach for software reliability analysis is given. The results show its usefulness for the design and evaluation of the early-stage software reliability modeling when failure data is not available. 展开更多
关键词 software reliability software reliability evaluation early-stage software reliability growth model stochastic reward nets Hierarchical model
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A component-based back-propagation reliability model with low complexity for complex software systems
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作者 聂鹏 Geng Ji Qin Zhiguang 《High Technology Letters》 EI CAS 2013年第3期273-282,共10页
Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-... Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-propagation reliability model(CBPRM)with low complexity for the complex software system reliability evaluation is presented in this paper.The proposed model is based on the artificial neural networks and the component reliability sensitivity analyses.These analyses are performed dynamically and assigned to the neurons to optimize the reliability evaluation.CBPRM has a linear increasing complexity and outperforms the state-based and the path-based reliability models.Another advantage of CBPRM over others is its robustness.CBPRM depends on the component reliabilities and the correlative sensitivities,which are independent from the software system structure.Based on the theory analysis and experiment results,it shows that the complexity of CBPRM is evidently lower than the contrast models and the reliability evaluating accuracy is acceptable when the software system structure is complex. 展开更多
关键词 software reliability evaluation component-based software system component reli-ability sensitivity artificial neural networks
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