并行遗传算法在软件可靠性优化中的应用

基于并行遗传算法将软件系统的可靠性优化问题表达为一类带约束条件的组合优化问题，并采用并行遗传算法中的岛屿模型和迁移策略，较好地改善了搜索性能。模拟实验表明：并行遗传算法有效地提高了运行速度和求解质量。     

基于约束条件的软件可靠性优化问题的研究

基于遗传算法,将软件系统的可靠性优化问题表达为一类带约束条件的组合优化问题,较好地改善了搜索性能。模拟实验表明：遗传算法有效地提高了运行速度和求解质量。     

一种面向汽车系统可靠性优化的任务分配方法*

对电子控制单元进行任务分配是汽车电子软件设计阶段一项非常重要的工作;以最大化系统可靠性为目标进行任务最优分配是一个NP-难问题。提出了一种改进的粒子群优化算法用于对任务进行近似最优分配以尽量提高系统的可靠性;通过在基本粒子群优化算法中引入一个新的变异操作有效提高了算法的收敛速度和解的精度。实验仿真表明该算法具有良好的有效性和可行性。     

基于组件的软件系统可靠性评估的不确定性研究

当前一些基于体系结构的软件可靠性模型,在操作剖面和组件可靠性中,不管这些模型是否准确,只要有相当多的不确定性存在,在计算软件可靠性时,就会存在较多的不确定性.若采用传统方法估算软件的可靠性,忽略了属于参数不确定性存在的差异,那么结果可能不准确.提出了一种新的基于体系结构的不确定性的分析方法,该方法适合大型复杂的基于组件的应用程序及整个软件生命周期.     

一种多维度的软件系统可靠性测试方法研究

传统的软件可靠性测试更多偏重于软件的功能方面。针对于这个不足之处,提出了结合操作剖面和性能测试的一种相对完善、全面的软件可靠性测试方法。归纳总结软件内部可靠性设计、外部高可用技术以及容灾恢复规范等诸多影响软件系统可靠性的因素,设计可靠性操作剖面要全面考虑这些因素。此方法是对传统方法的有用补充。最后通过一个案例简要介绍了该方法。     

一种改进的混沌优化算法

为了克服遗传算法的早熟现象以及混沌优化的搜索时间过长的缺点,将遗传算法、混沌优化和变尺度方法相结合,提出了一种改进的混沌优化算法.该算法利用混沌的随机性、遍历性和规律性来避免陷入局部极小值,从而也克服了遗传算法中的早熟现象,同时引入了变尺度方法提高该算法的搜索速度.本文还给出了算法的收敛性分析.对典型测试函数的仿真结果表明此算法优于变尺度混沌优化和遗传算法.     

直升机系统可靠性仿真研究

本文介绍直升机系统可靠性仿真研究及其相应的某型直升机可靠性仿真软件系统.首先讲述了系统开发背景;其次详细阐述可靠性数据的处理、可靠性模型的选择、建立及其参数估计方法,然后介绍了可靠性仿真软件的实现;最后给出了一个具体实例.直升机部件可靠性仿真,是直升机故障诊断及性能评估的重要参考.     

一种基于改进遗传算法的多峰函数优化研究

本文针对多峰函数优化问题,提出了一种基于排序的遗传算法,该算法对原有遗传算法的编码方式、选择算子、交叉算子及变异算子进行了改进,增加了灾变算子及精度调整环节。使搜索效率有了较大提高,较好地避免了系统,在实例运行中体现出优良特性。     

并行数据库复杂关系查询优化的一种方法

查询优化不仅是顺序数据库系统的重要组成部分，也是并行数据库的重要组成部分，而多个Ｊｏｉｎ操作的复杂关系数据库的查询经又是目前研究的 主要课题。     

一种基于遗传算法的查询优化方法

为帮助用户在丰富的网络资源中快速、准确地查询到所需要的信息,提出一种基于遗传算法的查询优化方法.其基本思想是首先根据词项与所有查询词的共现程度在相关文档集合中选取扩展词对初始查询进行扩展,然后利用遗传算法为扩展后的查询选择优化的权重.实验结果表明,新方法具有更高的查全率和查准率.     

一种新的软件测试方法的研究

提出基于蒙特卡罗的软件可靠性测试方法。它是软件工程中的一个新的研究领域,主要探讨蒙特卡罗方法和软件工程的交叉。一方面借鉴一些传统的软件测试方法,另一方面借助于蒙特卡罗方法,提出的一套全新的测试技术。     

一种软件可靠性测试方法研究

为了缩短软件测试周期,本文把马尔可夫链模型运用于软件可靠性测试中,提出了这一技术进行软件可靠性测试的方法。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。     

一种软件可靠性测试模型研究

在马尔可夫链模型的基础上,将测试问题转化为一个数学问题。通过建立软件的使用链,根据使用链进行序列抽样,产生测试用例,将软件测试结果的分析问题转化为一个经典概率问题。运用实例证明,这种技术具有一定的实用性和有效性。     

遗传算法在系统可靠性优化中的应用

研究性等价、体积和重量约束条件下，多级串联系统和桥式网络系统可靠性优化问题.使用遗传算法对该问题进行求解，利用基于排名的选择方法和最优保存策略，改善了遗传算法的收敛性能。计算机仿真实验结果表明，用遗传算法求解该问题是有效的。     

Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization

Software reliability growth model (SRGM) with testing-effort function (TEF) is very helpful for software developers and has been widely accepted and applied. However, each SRGM with TEF (SRGMTEF) contains some undetermined parameters. Optimization of these parameters is a necessary task. Generally, these parameters are estimated by the Least Square Estimation (LSE) or the Maximum Likelihood Estimation (MLE). We found that the MLE can be used only when the software failure data to satisfy some assumptions such as to satisfy a certain distribution. However, the software failure data may not satisfy such a distribution. In this paper, we investigate the improvement and application of a swarm intelligent optimization algorithm, namely quantum particle swarm optimization (QPSO) algorithm, to optimize these parameters of SRGMTEF. The performance of the proposed SRGMTEF model with optimized parameters is also compared with other existing models. The experiment results show that the proposed parameter optimization approach using QPSO is very effective and flexible, and the better software reliability growth performance can be obtained based on SRGMTEF on the different software failure datasets.     

基于可靠度的计算机系统优化问题的研究

分析了计算机系统硬件优化配置问题,给出了该问题的优化模型,并利用模拟退火算法和遗传退火算法对求解该问题进行了具体设计。通过实例仿真比较,遗传退火算法能得到比文献中算法和模拟退火算法更好的结果,表明算法是非常有效的。     

Some issues in software reliability assessment

The debate between those who prefer formal methods and those who advocate the use of reliability-growth models in the assessment of software reliability continues. Some issues arising from this conflict are raised and discussed, beginning with the definition of quantified software reliability. After arguing that the stochastic modelling approach is conceptually sound, its possible relationship with the structure of the software is discussed. Evidence that certain structural counts can be used in place of time as the argument in reliability growth models is reported. The question of the extent to which the many non-stochastic metrics now available contribute to software reliability quantification is aired. A relationship between reliability and a hierarchy of coverage metrics is reported, which may help to draw together the modellers and the testers.     

Survey of reliability and availability prediction methods from the viewpoint of software architecture

Many future software systems will be distributed across a network, extensively providing different kinds of services for their users. These systems must be highly reliable and provide services when required. Reliability and availability must be engineered into software from the onset of its development, and potential problems must be detected in the early stages, when it is easier and less expensive to implement modifications. The software architecture design phase is the first stage of software development in which it is possible to evaluate how well the quality requirements are being met. For this reason, a method is needed for analyzing software architecture with respect to reliability and availability. In this paper, we define a framework for comparing reliability and availability analysis methods from the viewpoint of software architecture. Our contribution is the comparison of the existing analysis methods and techniques that can be used for reliability and availability prediction at the architectural level. The objective is to discover which methods are suitable for the reliability and availability prediction of today’s complex systems, what are the shortcomings of the methods, and which research activities need to be conducted in order to overcome these identified shortcomings. The comparison reveals that none of the existing methods entirely fulfill the requirements that are defined in the framework. The comparison framework also defines the characteristics required of new reliability and availability analysis methods. Additionally, the framework is a valuable tool for selecting the best suitable method for architecture analysis. Furthermore, the framework can be extended and used for other evaluation methods as well.