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。     

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.     

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.     

软件测试数据的统计分析

软件可靠性评估是软件可靠性研究的重要问题,本文研究了软件测试数据的样本点序法,获得了软件可靠度的置信下限,证明了该置信限的最优性。最后给出一个实例说明该方法的可行性。     

虚拟振动测试分析系统的的软件可靠性测试分析

介绍了应用动态链接库DLL技术构成虚拟振动测试系统的原理方法和编程特点,分析了虚拟振动测试系统的软件可靠性测试分析方法,提出虚拟振动测试分析系统的软件可靠性评价指标,分析了软件故障产生原因以及提出减少故障发生方法。     

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。     

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。     

基于假设检验的软件可靠性模型预测精度比较

提出一种基于假设检验的软件可靠性模型预测精度比较方法，该方法将模型预测值与真实值的RE(相对误差)看作随机变量，利用假设检验思想度量模型预测精度，并给出多个模型之间预测精度的比较标准。     

软件质量保证技术研究综述

概述了软件可靠性研究的必要性，从软件开发过程管理，质量保证标准，测试技术、可靠性评估与预测以及形式化规范和验证等5个方面人出了软件质量问题的解决办法，并对所研究的成果做了介绍，最后指标了在统计测试，形式化方法方面有待进一步研究的问题。     

Designing a software reliability programme

Designing reliable software is becoming an ever increasing problem because the high cost of software is largely due to reliability problems. The costs of finding and fixing the errors, better known as maintenance and testing costs, account for as much as 80 per cent of the total cost of the final software product. Software developers now have an even greater interest in preventing errors from making their way into the software and finding the errors that are present in the early stages of development. Precise software design, coding and testing play an important role. This paper presents a management plan for implementing a software reliability programme at a small software industry where no reliability programme yet exists and no reliability programme is yet established.     

某测试软件输入模块的可靠性测试方法研究

采用黑盒测试方法对某数据采集系统的测试软件进行了测试.通过对软件需求和性能的分析,建立了软件的运行剖面和测试案例,进行了可靠性测试,得到了该软件输入模块的可靠性测试结果.     

TOPAAS: An Alternative Approach to Software Reliability Quantification

In the realm of safety related systems, a growing number of functions are realized by software, ranging from ‘firmware’ to autonomous decision‐taking software. To support (political) real‐world decision makers, quantitative risk assessment methodology quantifies the reliability of systems. The optimal choice of safety measures with respect to the available budget, for example, the UK (as low as reasonably practicable approach), requires quantification. If a system contains software, some accepted methods on quantification of software reliability exist, but none of them is generally applicable, as we will show. We propose a model bringing software into the quantitative risk assessment domain by introducing failure of software modules (with their probabilities) as basic events in a fault tree. The method is known as ‘TOPAAS’ (Task‐Oriented Probability of Abnormalities Analysis for Software). TOPAAS is a factor model allowing the quantification of the basic ‘software’ events in fault tree analyses. In this paper, we argue that this is the best approach currently available to industry. Task‐Oriented Probability of Abnormalities Analysis for Software is a practical model by design and is currently put to field testing in risk assessments of programmable electronic safety‐related systems in tunnels and control systems of movable storm surge barriers in the Netherlands. The TOPAAS model is constructed to incorporate detailed fields of knowledge and to provide focus toward reliability quantification in the form of a probability measure of mission failure. Our development also provides context for further in‐depth research. Copyright © 2013 John Wiley & Sons, Ltd.     

Change-points-based software scheduling

Software reliability literature consists of various change-point-based software reliability growth models and related release time problems. The primary assumption of the existing models is the existence of change-point before software release time only. This does not look practical as the testing team becomes more proficient in detecting the faults due to their continuous involvement in software development by the software release time. Hence the fault detection rate in the pre- and postrelease phase is not the same. To capture this change in fault detection rate in the pre- and postrelease testing phase, we propose a new software reliability modeling framework by considering two change-points during the software lifecycle; that is, there exists a change-point before release time and release time as a change-point. Further, in the last one-decade software firms have changed their strategy of stop testing the software after release and continue to test even after release to remove the number of faults to provide better user experiences. This phenomenon attracted academicians to develop theoretical as well empirical study on postrelease testing and formulation of related release time problem. In this paper, we propose a software cost model to determine optimal release and testing stop time considering under the assumption of two change-points as mentioned above. The proposed model is validated on real-life data set.     

Classification and Appraisement for Nonparametric Software Reliability Models

A taxonomy of software reliability models is developed that the models are classified as parametric and nonparametric models, and the nonparametric models are classified according to the mathematical methods they used. Then, a practical appraising index system for nonparametric software reliability models are put forward. The nonparametric software reliability models are classified into 5 classes, that is time series analysis models, grey theory forecasting models, artificial neural network models, wavelet ...     

基于TestQuest的嵌入式软件可靠性测试环境框架研究

嵌入式软件是软件中最难测试的一种软件,该文提出了一种嵌入式软件可靠性测试环境框架,分析了嵌入式软件测试与普通软件测试的异同。针对嵌入式软件难于测试的问题,运用仿真测试和自动化测试方法,并利用TestQuest工具辅助构建环境,重点介绍了框架中各个模块的功能、实时控制器的分层结构实现、上位机与实时控制器的通信协议编写方法,最后通过实例验证该平台有良好的适应性和易操作性。     

Computing Transition Probability in Markov Chain for Early Prediction of Software Reliability

Early prediction of software reliability provides basis for evaluating potential reliability during early stages of a project. It also assists in evaluating the feasibility of proposed reliability requirements and provides a rational basis for design and allocation decisions. Many researchers have proposed different approaches to predict the software reliability based on a Markov model. The transition probabilities in between the states of the Markov model are input parameters to predict the software reliability. In the existing approaches, these probabilities are either assumed on some knowledge or computed using analytical method, and hence, it does not give accurate predicted reliability figure. Some authors compute them using operational profile data, but that is possible only after the deployment of the software, and this is not early prediction. The work in this paper is devoted to demonstrate the computation of transition probability in the Markov reliability model taking a case study. The proposed approach has been validated on 47 sets of real data. Copyright © 2015 John Wiley & Sons, Ltd.     

Two Case Studies in Applying Statistical Models in Software Development

We present two case studies in software testing to illustrate two different goals of software reliability analyses. The first case study is about administrative software of an insurance company, while the second one is on an issue of national interest in the Netherlands: safety of software control of a closable dam as part of a sea flood protection system. We pay attention to practical and methodological aspects that often are ignored or not correctly treated in software reliability analyses. In particular, we provide pointers to recent statistics literature that are relevant for software reliability.     

Multinomial-exponential reliability function: a software reliability model

The multinomial-exponential reliability function (MERF) was developed during a detailed study of the software failure/correction processes. Later on MERF was approximated by a much simpler exponential reliability function (EARF), which keeps most of MERF mathematical properties, so the two functions together makes up a single reliability model. The reliability model MERF/EARF considers the software failure process as a non-homogeneous Poisson process (NHPP), and the repair (correction) process, a multinomial distribution. The model supposes that both processes are statistically independent.The paper discusses the model's theoretical basis, its mathematical properties and its application to software reliability. Nevertheless it is foreseen model applications to inspection and maintenance of physical systems. The paper includes a complete numerical example of the model application to a software reliability analysis.     

Impacts of networking effects on software reliability growth processes: A multi‐attribute utility theory approach

Software reliability growth models, which are based on nonhomogeneous Poisson processes, are widely adopted tools when describing the stochastic failure behavior and measuring the reliability growth in software systems. Faults in the systems, which eventually cause the failures, are usually connected with each other in complicated ways. Considering a group of networked faults, we raise a new model to examine the reliability of software systems and assess the model's performance from real‐world data sets. Our numerical studies show that the new model, capturing networking effects among faults, well fits the failure data. We also formally study the optimal software release policy using the multi‐attribute utility theory (MAUT), considering both the reliability attribute and the cost attribute. We find that, if the networking effects among different layers of faults were ignored by the software testing team, the best time to release the software package to the market would be much later while the utility reaches its maximum. Sensitivity analysis is further delivered.