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。     

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。     

计算机软件测试应用探讨

随着我国计算机技术的飞速发展,计算机软件的重要性越来越突出。计算机软件测试虽然与计算机性能没有直接的关联性,但可以有效的减少错误,提高软件稳定性,保证计算机的功能性。文章主要从软件工程学来阐述计算机的软件测试、测试方法以及管理应用技术。     

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.     

软件测试在软件开发过程中的应用研究

随着信息时代的到来,软件在人们的生产生活中发挥着越来越大的作用。因此,为减少软件运行过程中的错误,保证软件质量,开发人员需在不同阶段对软件性能进行测试。文章研究了软件测试在软件开发过程中的应用,以期为软件的开发提供参考。     

软件开发中单元测试常用方法浅析

不论采用什么技术和方法,软件中仍然会有错。软件测试的目的是发现程序中的错误,是为了证明程序有错,而不是证明程序无错。软件测试的目的之一就是尽可能早地发现软件中存在的错误,所以单元测试很重要。重点论述单元测试中最常用到的静态测试技术,也论述黑盒测试与白盒测试等动态测试技术的运用。     

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。     

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。     

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。     

An architectural model for software reliability quantification: sources of data

Software reliability assessment models in use today treat software as a monolithic block. An aversion towards ‘atomic' models seems to exist. These models appear to add complexity to the modeling, to the data collection and seem intrinsically difficult to generalize. In 1997, we introduced an architecturally based software reliability model called FASRE. The model is based on an architecture derived from the requirements which captures both functional and nonfunctional requirements and on a generic classification of functions, attributes and failure modes. The model focuses on evaluation of failure mode probabilities and uses a Bayesian quantification framework. Failure mode probabilities of functions and attributes are propagated to the system level using fault trees. It can incorporate any type of prior information such as results of developers' testing, historical information on a specific functionality and its attributes, and, is ideally suited for reusable software. By building an architecture and deriving its potential failure modes, the model forces early appraisal and understanding of the weaknesses of the software, allows reliability analysis of the structure of the system, provides assessments at a functional level as well as at a systems' level. In order to quantify the probability of failure (or the probability of success) of a specific element of our architecture, data are needed. The term element of the architecture is used here in its broadest sense to mean a single failure mode or a higher level of abstraction such as a function. The paper surveys the potential sources of software reliability data available during software development. Next the mechanisms for incorporating these sources of relevant data to the FASRE model are identified.     

Combined hardware and software aspects of reliability

This paper presents the similarities and differences between hardware, software and system reliability. Relative contributions to system failures are shown for software and hardware and failure and recovery propensities are also discussed. Reliability, availability and maintainability (RAM) concepts have been broadly developed for software reliability than hardware reliability. Extending these software concepts to hardware and system reliability helps in examining the reliability of complex systems. The paper concludes with assurance techniques for defending against faults. Most of the techniques discussed originate in software reliability but apply to all aspects of a system. Also, the effects of redundancy on overall system availability are shown.     

Fault-tolerant embedded system design and optimization considering reliability estimation uncertainty

In this paper, we model embedded system design and optimization, considering component redundancy and uncertainty in the component reliability estimates. The systems being studied consist of software embedded in associated hardware components. Very often, component reliability values are not known exactly. Therefore, for reliability analysis studies and system optimization, it is meaningful to consider component reliability estimates as random variables with associated estimation uncertainty. In this new research, the system design process is formulated as a multiple-objective optimization problem to maximize an estimate of system reliability, and also, to minimize the variance of the reliability estimate. The two objectives are combined by penalizing the variance for prospective solutions. The two most common fault-tolerant embedded system architectures, N-Version Programming and Recovery Block, are considered as strategies to improve system reliability by providing system redundancy. Four distinct models are presented to demonstrate the proposed optimization techniques with or without redundancy. For many design problems, multiple functionally equivalent software versions have failure correlation even if they have been independently developed. The failure correlation may result from faults in the software specification, faults from a voting algorithm, and/or related faults from any two software versions. Our approach considers this correlation in formulating practical optimization models. Genetic algorithms with a dynamic penalty function are applied in solving this optimization problem, and reasonable and interesting results are obtained and discussed.     

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.     

Discrete Nonhomogeneous Poisson Process Software Reliability Growth Models Based on Test Coverage

To incorporate the effect of test coverage, we proposed two novel discrete nonhomogeneous Poisson process software reliability growth models in this article using failure data and test coverage, which are both regarding the number of executed test cases instead of execution time. Because one of the most important factors of the coverage‐based software reliability growth models is the test coverage function (TCF), we first discussed a discrete TCF based on beta function. Then we developed two discrete mean value functions (MVF) integrating test coverage and imperfect debugging. Finally, the proposed discrete TCF and MVFs are evaluated and validated on two actual software reliability data sets. The results of numerical illustration demonstrate that the proposed TCF and the MVFs provide better estimation and fitting under comparisons. Copyright © 2012 John Wiley & Sons, Ltd.     

液体火箭发动机试验流量测量系统可靠性评定

针对液体发动机可靠性评定的研究现状,从性能可靠性和结构可靠性两个维度对流量测量系统的可靠性进行评定。给出了测量系统性能可靠性的定义,将测量数据视为正态分布,通过区间估计的方法计算单侧可靠性置信下限。给出了测量系统结构可靠性的定义。根据流量测量系统串联可靠性框图,对将指数寿命失效型试验信息转换为二项成败型试验信息。采用L-M法(Lindstrom-Maddens),结合查表和线性插值法求解结构可靠性置信下限。该测量系统可靠性评估方法对行业内测量技术人员具有重要的参考意义。     

Software dependability models under memory faults with application to a digital system in nuclear power plants

In this work, software dependability under memory faults in the operational phase is predicted by two models: an analytic model and the stochastic activity network (SAN) model. The analytic model is based on the simple reliability theory and the graph theory, which represents the software as a graph composed of nodes and arcs. Through proper transformation, the graph can be reduced to a simple two-node graph from which software reliability can be derived. The SAN model permits the representation of concurrency, timeliness, fault tolerance, and degradable performance of the system and provides a means for determining the stochastic behavior of a software.Using these models, we predict the reliability of an application software in a digital system, Interposing Logic System (ILS), in a nuclear power plant and show the sensitivity of software reliability to major physical parameters which affect software failure in the normal operation phase. It is found that the effects of hardware faults on software failure should be considered for the accurate prediction of software dependability in the operation phase.     

A goal oriented approach to software testing

There is a tendency to distribute the testing and validation effort in a software project uniformly over all system functions. However, to improve systems reliability and safety, testing effort must be focused on the functions with the highest failure consequences. This paper describes a method that computes the number of test cases given the accepted risk levels for each function. Input to the method are the total set of functions for the system, the set of possible accidents and their consequences plus the subset of accidents that can be caused by a failure in one particular function. Failure consequences and functions usage are then used to find the Potential Annual Loss Exposure (PALE) by using a simple diagram developed by AFSC. Given the PALE value, system functions can be ranked according to their risk. It is then possible to set goals for their failure probabilities and to compute the number of test cases needed for each function.     

面向维修的机械系统可靠度预测与仿真研究

机电产品在服役期间因零件失效而产生故障,重组维修破坏了原有的系统可靠性模型,因而需要对设备可靠性问题重新进行研究和评价。基于机电系统中零件的失效时间分布密度函数,研究了在重组维护过程中机电系统服役期间零件年龄结构的分布规律,发展了机电系统可靠性数学模型。通过仿真研究,探讨了系统服役期间年龄结构、可靠度和失效率的发展规律,定量地研究了失效时间分布密度函数的参数对系统可靠度的影响。这对于评估机械系统的可靠性和全生命周期的失效率,制定合理的维修策略具有重要意义。     

An analytical framework for reliability growth of one-shot systems

In this paper, we introduce a new reliability growth methodology for one-shot systems that is applicable to the case where all corrective actions are implemented at the end of the current test phase. The methodology consists of four model equations for assessing: expected reliability, the expected number of failure modes observed in testing, the expected probability of discovering new failure modes, and the expected portion of system unreliability associated with repeat failure modes. These model equations provide an analytical framework for which reliability practitioners can estimate reliability improvement, address goodness-of-fit concerns, quantify programmatic risk, and assess reliability maturity of one-shot systems. A numerical example is given to illustrate the value and utility of the presented approach. This methodology is useful to program managers and reliability practitioners interested in applying the techniques above in their reliability growth program.