软件可靠性测试技术研究

文章分析了软件可靠性测试的过程、可靠性测试中涉及的基本参数及计算方法、软件运行剖面的概念和获取运行剖面的步骤、测试用例的选择方法、软件可靠性测试模型的作用和建立方法。     

软件增长测试中可靠性评估方案的研究

软件可靠性评估在软件测试中起着举足轻重的作用.本文研究了软件增长测试中可靠性评估的过程.给出了判断软件可靠性是否增长的方法,通过比较常用的M-O模型和J-M模型给出了如何选取合适的可靠性评估模型的方法,以及判断选择的拟合模型的准确性的方法,并根据选取的拟合评估模型估测出软件可靠性的一些参数,最终提出了一种新的软件增长测试中可靠性评估方案,用于指导软件可靠性测试的顺利进行.     

Application of a software reliability model to decide software release time

In this paper, using a Binomial reliability model, we formulate the optimal software release time problem as a probabilistic dynamic programming. Using some properties of the cost functions associated with this problem, we develop an efficient algorithm to obtain the optimal release time decision.     

Needed resources for software module test, using thehyper-geometric software reliability growth model

Considerable testing resources are required during software module testing. This paper, based on the `hyper-geometric distribution software reliability growth model' (HGDM) investigates two optimal resource allocation (OPT/RA) problems in software module testing: (1) minimization of the number of software faults (NSF) still undetected in the system after testing, given a fixed amount of testing resources; and (2) minimization of the total amount of testing resources required, given the NSF still undetected in the system after testing. Based on the concepts of average allocation and proportional allocation, two simple allocation methods are introduced. Experimental results show that the OPT/RA method can improve the quality and reliability of the software system much more than the simple allocation methods. Therefore, the OPT/RA method is very efficient for solving the `testing resource allocation' problem     

Discussion of de-embedding techniques using time-domain analysis

De-embedding is a mathematical inverse operation used in network analysis to separate and obtain differences. The time-domain analysis process saparates reflections, identifies them, and allows selected reflections to be analyzed. This paper uses both techniques to explain and illustrate the results.     

软件支持过程对软件测试的影响

越来越多的软件组织开始重视软件测试活动,希望借此改善软件质量,提高软件可靠性。通过分析软件测试活动与软件支持过程的关系,论述了软件支持过程对测试活动的影响,提出改进软件支持过程以保障软件测试有效实施的观点。     

Using a software reliability model to design a telecommunicationssoftware architecture

The author proposes a software reliability model for a large real-time telecommunications software architecture. Some simple examples of the critical components of the software architecture and their dependencies are described. The component dependencies permit the propagation of faults from the component in which the fault originates to the other components. This propagation can cause failures in the chain (or in the tree) of components. Detection and failures depends on the tests executed or on the number and type of customer requests. An error can occur in any component. This error can be caused by a fault that propagated from another component or it can be a fault that originates in that component. The error can be traced through the component-dependency chain (or tree) to repair all the faults that are associated with that error. The software reliability model guides the design of the software architecture     

基于决策树的软件可靠性模型选择

软件可靠性建模是软件可靠性评估的主要方法之一。现在还没有一个可适用于所有软件项目的通用模型,所以可靠性模型的选择已成为一个重要的研究方向。决策树是数据挖掘的一种算法。文中首先介绍数据挖掘与软件可靠性模型选择的结合应用概念,然后重点分析决策树的生成算法。最后以一组数据仿真决策树生成过程,并验证此方法的可行性和准确性。     

Effect of code coverage on software reliability measurement

Existing software reliability-growth models often over-estimate the reliability of a given program. Empirical studies suggest that the over-estimations exist because the models do not account for the nature of the testing. Every testing technique has a limit to its ability to reveal faults in a given system. Thus, as testing continues in its region of saturation, no more faults are discovered and inaccurate reliability-growth phenomena are predicted from the models. This paper presents a technique intended to solve this problem, using both time and code coverage measures for the prediction of software failures in operation. Coverage information collected during testing is used only to consider the effective portion of the test data. Execution time between test cases, which neither increases code coverage nor causes a failure, is reduced by a parameterized factor. Experiments were conducted to evaluate this technique, on a program created in a simulated environment with simulated faults, and on two industrial systems that contained tenths of ordinary faults. Two well-known reliability models, Goel-Okumoto and Musa-Okumoto, were applied to both the raw data and to the data adjusted using this technique. Results show that over-estimation of reliability is properly corrected in the cases studied. This new approach has potential, not only to achieve more accurate applications of software reliability models, but to reveal effective ways of conducting software testing     

Data stability in an application of a software reliability model

The Goel-Okumoto (1979) model of reliability growth is applied to the failure data for a large software development project. This is done by fitting the model parameters to the error counts and test times, which are periodically tabulated. In the early phases of system testing, the problem of inaccurate estimation due to insufficient reliability growth occurs. A simple test is devised to measure the stability of the data with respect to this problem. In practice, such a test on the data can be used to determine when system testing has sufficiently progressed to allow one to expect reasonable estimates from reliability growth models     

A new model of software reliability prediction

To start with, a new generalized structure of basic equations of software reliability has been defined. In this new structure, the software reliability has been defined in terms of execution time T and operational time t. Then, a new model of software reliability has been proposed and fitted into the new structure.     

A Bayes empirical-Bayes model for software reliability

The authors present a model for the behavior of software failures. Their model fits into the general framework of empirical Bayes problems; however, they take a proper Bayes approach for inference by viewing the situation as a Bayes empirical-Bayes problem. An approximation due to D.V. Lindley (1980) plays a central role in the analysis. They show that the Littlewood-Verall model (1973) is an empirical Bayes model and discuss a fully Bayes analysis of it using the Bayes empirical-Bayes setup. Finally, they apply both models to some actual software failure data and compare their predictive performance     

一种改进的NHPP软件可靠性模型

软件可靠性模型是定量评估软件质量的重要手段,通过综合分析软件故障检测率及故障引入率建立改进的NHPP软件可靠性模型,并对可靠度进行分析,证明所提模型的有效性,最后通过对现有的数据进行分析,并与经典模型进行比较,证明所提模型的优良性。     

On program testing issues in software reliability—A survey

On account of various difficulties encountered with establishing the proof of correctness for software systems; the program testing seems to be the only sure way to prevent malfunctions from occurrence and thus to improve the software reliability. Whereas program proving is a reductive process; program testing is an affirmative process since everything done in testing can potentially contribute information about the quality of program being tested. Testing is the process of executing programs with representative input data or conditions, for which the correct results are known to determine whether incorrect results occur. This paper makes an attempt to provide a cross-section of current program testing technology—ranging from philosophical issues to research and development concepts to the extent that the known literature permits.     

某嵌入式软件可靠性仿真测试系统设计与实现

根据软件可靠性要求,在对某嵌入式控制软件进行功能需求和组成结构分析的基础上,设计实现了一种嵌入式可靠性仿真测试系统。该系统主要是针对某嵌入式被测系统建立仿真测试环境,对被测系统中的嵌入式软件进行可靠性测试。文章重点对系统设计中的需求分析、系统构成和构成系统各个模块的设计方法进行了阐述。最后通过测试实践验证了系统在实际嵌入式软件可靠性测试中具有较高的使用价值,并为其他类嵌入式软件的可靠性测试提供了一种较为灵活的思路。     

A general software reliability model for performance prediction

In this paper we give a general Markov process formulation for a software reliability model and present expressions for software performance measures. We discuss a general model and derive the maximum likelihood estimates for the required parameters of this model. The generality of this model is demonstrated by showing that the Jelinski-Moranda model and the Non-Homogeneous Poisson Process (NHPP) model are both very special cases of our model. In this process we also correct some errors in a previous paper of the NHPP model.     

The new applications of the hypergeometric distribution model on software reliability

In the past, the hypergeometric distribution model might only be used for estimating the error number of software. However, this paper shows how to use it for calculating the reliability and the MTBF of software quantitatively.     

The impact of software enhancement on software reliability

This paper exploits the `relationship between functional-enhancement (FE) activity and the distribution of software defects' to develop a discriminant model that identifies high-risk program modules, `FE activity' and `defect data captured during the FE of a commercial programming language processing utility' serve to fit and test the predictive quality of this model. The model misclassification rates demonstrate that FE information is sufficient for developing discriminant models identifying high-risk program modules. Consideration of the misclassified functions leads us to suggest that: (1) the level of routines in the calling hierarchy introduces variation in defect distribution; and (2) the impact of a defect indicates the risk that it presents. Thus consideration of defect impact can improve the discriminant results     

Electromagnetic wave effects on microwave transistors using afull-wave time-domain model

A detailed full-wave time-domain simulation model for the analysis of electromagnetic effects on the behavior of the submicrometer-gate field-effect transistor (FET's) is presented. The full wave simulation model couples a three-dimensional (3-D) time-domain solution of Maxwell's equations to the active device model. The active device model is based on the moments of the Boltzmann's transport equation obtained by integration over the momentum space. The coupling between the two models is established by using fields obtained from the solution of Maxwell's equations in the active device model to calculate the current densities inside the device. These current densities are used to update the electric and magnetic fields. Numerical results are generated using the coupled model to investigate the effects of electron-wave interaction on the behavior of microwave FET's. The results show that the voltage gain increases along the device width. While the amplitude of the input-voltage wave decays along the device width, due to the electromagnetic energy loss to the conducting electrons, the amplitude of the output-voltage wave increases as more and more energy is transferred from the electrons to the propagating wave along the device width. The simulation confirms that there is an optimum device width for highest voltage gain for a given device structure. Fourier analysis is performed on the device output characteristics to obtain the gain-frequency and phase-frequency dependencies. The analysis shows a nonlinear energy build-up and wave dispersion at higher frequencies