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
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
An approach for web server cluster(WSC)reliability and degradation process analysis is proposed.The reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson p...An approach for web server cluster(WSC)reliability and degradation process analysis is proposed.The reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson processes(NHPPs).The arrival rate of each NHPP corresponds to the system software failure rate which is expressed using Cox s proportional hazards model(PHM)in terms of the cumulative and instantaneous load of the software.The cumulative load refers to software cumulative execution time,and the instantaneous load denotes the rate that the users requests arrive at a server.The result of reliability analysis is a time-varying reliability and degradation process over the WSC lifetime.Finally,the evaluation experiment shows the effectiveness of the proposed approach.展开更多
According to the consequences of software failures, software faults remaining in safety-critical systems can be classified into two sets： common faults and fatal faults. Common faults cause slight loss when they are ...According to the consequences of software failures, software faults remaining in safety-critical systems can be classified into two sets： common faults and fatal faults. Common faults cause slight loss when they are activated. A fatal fault can lead to significant loss, and even damage the safety-crltical system entirely when it is activated. A software reliability growth model for safety-critical systems is developed based on G - 0 model. And a software cost model is proposed too. The cost model considers maintenance and risk costs due to software failures. The optimal release policies are discussed to minimize the total software cost. A numerical exampie is provided to illustrate how to use the results we obtained.展开更多
基金Supported by the National Natural Science Foundation of China(No.60973118,60873075)
文摘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.
基金This work was supported in part by the Ph.D.Programs Foundation of Ministry of Education of China under
文摘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.
基金The National Natural Science Foundation of China(No.61402333,61402242)the National Science Foundation of Tianjin(No.15JCQNJC00400)
文摘An approach for web server cluster(WSC)reliability and degradation process analysis is proposed.The reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson processes(NHPPs).The arrival rate of each NHPP corresponds to the system software failure rate which is expressed using Cox s proportional hazards model(PHM)in terms of the cumulative and instantaneous load of the software.The cumulative load refers to software cumulative execution time,and the instantaneous load denotes the rate that the users requests arrive at a server.The result of reliability analysis is a time-varying reliability and degradation process over the WSC lifetime.Finally,the evaluation experiment shows the effectiveness of the proposed approach.
基金Sponsored by the Ph.D. Programs Foundation of Ministry of Education of China (Grant No. 20020213017).
文摘According to the consequences of software failures, software faults remaining in safety-critical systems can be classified into two sets： common faults and fatal faults. Common faults cause slight loss when they are activated. A fatal fault can lead to significant loss, and even damage the safety-crltical system entirely when it is activated. A software reliability growth model for safety-critical systems is developed based on G - 0 model. And a software cost model is proposed too. The cost model considers maintenance and risk costs due to software failures. The optimal release policies are discussed to minimize the total software cost. A numerical exampie is provided to illustrate how to use the results we obtained.
