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Flexible software reliability growth modeling based on stochastic differential equations for distributed development environment

机译:基于随机发展环境的随机微分方程的灵活软件可靠性增长建模

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摘要

At present, software development environment has been changing into new development paradigm in such client/server systems and distributed development by using network computing technologies. Software systems produced in such distributed one tend to increase in size and complexity. If the size of the software system is large, the number of faults detected during the testing phase becomes large, and the change of the number of faults which are detected and removed through each debugging becomes sufficiently small compared with the initial fault content at the beginning of the testing. In this paper, we propose a software reliability growth model describing a fault-detection process during the system testing phase of the distributed development environment by applying a mathematical technique of stochastic differential equations of an Ito type. Considering the conventional stochastic differential equation model for distributed development environment, we derive a flexible stochastic differential equation model, arid show numerical examples with sensitivity analyses on the weight parameter.
机译:目前,软件开发环境在此类客户/服务器系统中的新开发范式并通过使用网络计算技术在分布式开发中变化。在这种分布式中产生的软件系统往往会增加尺寸和复杂性。如果软件系统的大小很大,则在测试阶段期间检测到的故障数变大,并且通过每个调试检测和删除的故障数量的变化与开始时的初始故障内容相比,检测到和删除的故障的数量变得足够小测试。在本文中,我们通过应用ITO类型的随机微分方程的数学技术来提出描述了分布式开发环境的系统测试阶段的故障检测过程的软件可靠性增长模型。考虑到分布式开发环境的传统随机微分方程模型,我们得出了一种灵活的随机微分方程模型,干旱显示了对权重参数的灵敏度分析的数值例子。

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