马尔可夫链模型在软件可靠性测试中的应用

现行的软件可靠性分析方法禁锢了人们从更简单层次对软件系统的可靠性进行研究。基于上述认识,为了缩短软件测试周期,文中提出了一种新的软件可靠性测试分析方法。该方法把马尔可夫链模型运用于软件可靠性测试中,在测试过程中使用了新的评判准则分析测试结果,通过实例证明了该评判准则的实用性和有效性。从而为更快速地评估软件的可靠性提供了可能。     

马尔科夫链模型在软件可靠性测试中的应用研究

现行的软件可靠性分析方法禁锢了人们从更简单层次对软件系统的可靠性进行研究.基于上述认识,为了缩短软件测试周期,文中提出了一种新的软件可靠性测试分析方法.该方法把马尔科夫链模型运用于软件可靠性测试中,在测试过程中使用了新的评判准则分析测试结果,通过实例证明了该评判准则的实用性和有效性,从而为更快速地评估软件的可靠性提供了可能.     

软件分域测试可靠性评估的注记

软件可靠性评估是软件可靠性研究的重要问题。文中通过反例证明了分域测试的Thayer-Lipow-Nelson评估方法是不正确的，将样本点百序法用于分域产生可靠性评估，获得了软件可靠性置信下限。最后给出一个实例说明该方法的可行性。     

软件无失效测试数据的统计分析

软件可靠性估计是软件可靠性研究的重要问题之一，文中对分布式软件系统可靠性的评估方法进行了研究．给出了软件系统可靠度的最优置信下限．最后以某大型软件的评估为例，说明该方法的应用。     

关于软件可靠性测试的若干问题

软件可靠性测试是软件测试的一种形式,它强调软件测试与软件可靠性之间的定量关系,旨在定量改进和评估软件可靠性。从数学角度严格量化软件测试与软件可靠性之间的关系是一件困难的事情。本文举例说明软件可靠性测试中的几个问题,包括软件缺陷的估计、软件测试过程的数学建模、以及软件可靠度的最优估计等。由此可知,软件可靠性测试涉及到不同领域的知识和多种数学工具。     

计算机软件可靠性设计研究

本文介绍了软件可靠性设计的基本概念,软件故障产生的机理,软件质量的可靠性参数,并且着重介绍了软件可靠性设计方法。     

浅析计算机软件可靠性设计

本文介绍了软件可靠性设计的基本概念,软件故障产生的机理,软件质量的可靠性参数,并且着重介绍了软件可靠性设计方法。     

基于概率论的测试用例优化技术研究

软件可靠性测试是软件工程中的一个新的研究领域.为了缩短软件测试周期,测试用例的生成是关键.基于马尔可夫链模型,提出了一种测试用例优化技术,该理论采用适应度比例的概率方法进行优化.通过例子证明.该方法在产生均匀、优化的测试用例方面是有效的.     

多任务处理软件可靠性分配模型研究及应用

对各类软件可靠性分配模型研究基础上,针对多任务处理软件提出一种基于任务的可靠性分配模型及技术方法,并以某多任务处理软件为实例进行指标分配验证,分配结果表明,在满足系统或软件任务书可靠性的情况下,能够实现多任务处理软件可靠性指标分配。     

故障诊断专家系统软件的测试

提高软件可靠性的关键是力求减少软件中的错误。软件的错误可能来源于软件寿命周期内的各个阶段,测试工作在软件生存期中占有重要位置。本文主要讨论一个自行高炮故障诊断专家系统软件的测试。文中介绍了该软件的功能、组成、故障分离过程和测试方法。通过该软件测试的运行,以期达到减少软件中的错误,提高软件可靠性,有效地解决现代军事装备的复杂性同管理体系,人员素质之间的矛盾。     

Reliability‐based Optimal Maintenance Scheduling by Considering Maintenance Effect to Reduce Cost

A new reliability‐based optimal maintenance scheduling method is presented that considers the effect of maintenance in reducing costs. An ordering list of element maintenance effects with various maintenance‐interval types is constructed. By means of this ordering list, reliability‐based optimal maintenance scheduling for simple reliability structures and composite reliability systems is then carried out. The properties of the proposed method, such as the evaluation of maintenance cost reduction, the simplicity of the proposed method by sacrificing system availability within the allowance method, the operation decision based on the optimal maintenance schedule, etc., are discussed. With simulations, the effectiveness of the proposed method is verified. Copyright © 2005 John Wiley & Sons, Ltd.     

A model for Bayesian software reliability analysis

Two problems which are of great interest in relation to software reliability are the prediction of future times to failure and the calculation of the optimal release time. An important assumption in software reliability analysis is that the reliability grows whenever bugs are found and removed. In this paper we present a model for software reliability analysis using the Bayesian statistical approach in order to incorporate in the analysis prior assumptions such as the (decreasing) ordering in the assumed constant failure rates of prescribed intervals. We use as prior model the product of gamma functions for each pair of subsequent interval constant failure rates, considering as the location parameter of the first interval the failure rate of the following interval. In this way we include the failure rate ordering information. Using this approach sequentially, we predict the time to failure for the next failure using the previous information obtained. Using also the relevant predictive distributions obtained, we calculate the optimal release time for two different requirements of interest: (a) the probability of an in‐service failure in a prescribed time t; (b) the cost associated with a single or more failures in a prescribed time t. Finally a numerical example is presented. Copyright © 2000 John Wiley & Sons, Ltd.     

基于响应面法和Morgenstern-Price法土坡可靠度计算方法

基于响应面法,建立了一种高效的边坡可靠度指标和失效概率近似计算方法。该法在构造响应面函数时,抽样点计算采用Morgenstern-Price法取代传统费时的有限单元法,大大降低了计算工作量。利用Monte-Carlo随机抽样原理,提出了一种能同时确定边坡最危险非圆弧滑动面和最小可靠度指标的随机搜索新算法。该文给出的两个算例验证了方法的实用性和可靠性,其计算结果同时表明:当分别以最小可靠度指标和最小中值安全系数为目标函数时,搜索到的边坡最危险滑动面相差较大。最后,探讨了土性指标(c,φ)的分布概型及相关性对边坡可靠度计算结果的影响。     

Response surface method based on uniform design and weighted least squares for non-probabilistic reliability analysis

The non-probabilistic reliability theory is a promising methodology for implementing structural reliability analysis in case of scarce statistical data. One of the main obstacles to implement non-probabilistic reliability analysis is the implication of the limit state function (LSF) for complex structures. This paper aims to establish a surrogate model of the LSF with higher simulation precision, and whereby proposes a response surface method based on the combination of uniform design (UD) and weighted least squares (WLS). At first, the UD method is selected as the sampling method of interval variables to realize the uniform space-filling of the initial samples, and the sample set is updated by gradually adding the approximate optimal points to increase the sampling density of critical domain. Then, the WLS method is applied to improve the precision of the response surface by adjusting the importance of samples to the function fitting. Finally, a method of constructing sample weights is developed. Two examples are applied to validate the feasibility and efficiency of the proposed method. Results show that the proposed method is effective for non-probabilistic reliability analysis of complex structures owning to high computational precision and low computational cost in both numerical and case study.     

船用辅机浮筏动态特性有限元分析

本文采用ANSYS软件对一船用辅机浮筏的固有振动特性、隔振效果和抗冲击性能进行了数值分析。浮筏装配后对其隔振效果进行了测试 ,测试结果表明本文的数值分析方法是可信的 ,所得结论可供工程设计参考。     

Feedback method of production ordering system in multi-stage production and inventory systems

This paper deals with the problem of developing a production ordering system which maintains high reliability and productivity of multi-stage production and inventory systems with capacity-constraint and machine breakdown. In this paper, two ‘push type’ production ordering systems (Matsuura and Soshiroda 1981) are proposed according to information feedback methods. The influence of forecasting error, the difference between forecasted demands, down-time, and the backlog caused by the restriction of production capacity, upon the production and inventory levels is analysed by each production ordering system. The results indicate that, in designing an effective production ordering system, a feedback method must be chosen according to the conditions of the average loading ratio, the down-time, and the autocorrelation coefficient of demand.     

硫酸中阳极氧化制备Al2O3多孔模板的BPANN模拟

采用24组硫酸阳极氧化多孔膜的样本数据建立BP神经网络模型,得到了多孔膜孔有序度与硫酸阳极氧化参数之间的最优关系,经检验该模型的预测结果与实测结果相一致.表明BPANN 是硫酸阳极氧化制备多孔膜孔有序度的较好的预测模型.     

Cr替代Mn对La0.4Ca0.6MnO3磁性质的影响

用固相反应法制备了La0.4Ca0.6Mn1-xCrxO3(x=0.00,0.02,0.04,0.06,0.08,0.10,0.15)多晶样品,通过X射线衍射(XRD)图谱、磁化强度-温度(M-T)曲线、电子自旋共振(ESR)谱线,研究了Cr替代Mn对La0.4Ca0.6MnO3磁性质的影响.实验结果表明:La0.4Ca0.6MnO3存在复杂的磁结构,在258 K出现电荷有序相,从175 K到50 K,产生强关联CO-AFM(电荷有序?反铁磁)相,温度降到41 K左右出现自旋玻璃态;当替代量x≥0.06时,电荷有序相被融化;当x≥0.10时,自旋玻璃态被融化.对实验结果进行了初步解释:电荷有序相被融化主要原因是Cr3+与Mn4+具有相同的电子结构,Cr3+替代Mn3+破坏了CE型反铁磁的自旋序,从而引起电荷序的坍塌,实验证明了电荷序CE型反铁磁体系中,电荷序和自旋序之间存在强耦合相互作用;自旋玻璃态的融化,是由于Cr替代Mn破坏了自旋玻璃态的生成条件,即反铁磁背景下有少量铁磁成分.     

基于Bayes法的电主轴极小子样可靠性研究

针对长寿命的磨削电主轴极小子样的可靠性评估问题,提出了Bayes结合虚拟增广样本的分析方法。首先,在Bayes法基本流程的指导下,研究了基于Bayes法的磨削电主轴可靠性评估方法。根据定时截尾试验的原则对电主轴进行可靠性试验,应用Bayes法结合磨削电主轴试验样本的可靠性试验数据,综合虚拟增广样本法对其可靠性进行评估,最终获得电主轴的可靠性评估结果。最后,将基于Bayes法与基于伪寿命分布法的磨削电主轴极小子样可靠性评估结果进行比较,以验证基于Bayes法可靠性评估理论的合理性。     

A Bayesian model averaging method for software reliability modeling and assessment

The software reliability modeling is of great significance in improving software quality and managing the software development process. However, the existing methods are not able to accurately model software reliability improvement behavior because existing single model methods rely on restrictive assumptions and combination models cannot well deal with model uncertainties. In this article, we propose a Bayesian model averaging (BMA) method to model software reliability. First, the existing reliability modeling methods are selected as the candidate models, and the Bayesian theory is used to obtain the posterior probabilities of each reliability model. Then, the posterior probabilities are used as weights to average the candidate models. Both Markov Chain Monte Carlo (MCMC) algorithm and the Expectation–Maximization (EM) algorithm are used to evaluate a candidate model's posterior probability and for comparison purpose. The results show that the BMA method has superior performance in software reliability modeling, and the MCMC algorithm performs better than EM algorithm when they are used to estimate the parameters of BMA method.