A vector Markov model for structural coverage growth and the number of failure occurrences

Michael Grottke
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引用次数: 12

Abstract

Most software reliability growth models specify the expected number of failures experienced as a function of testing effort or calendar time. However, there are approaches to model the development of intermediate factors driving failure occurrences. This paper starts out with presenting a model framework consisting of four consecutive relationships. It is shown that a differential equation representing this framework is a generalization of several finite failures category models. The relationships between the number of test cases executed and expected structural coverage, and between expected structural coverage and the expected number of failure occurrences are then explored further. A vector Markov model allowing for partial redundancy in sampling code constructs is developed. The model bridges the gap between setups related to operational testing and systematic testing, respectively. Two extensions of the partial redundancy model considering the development of the number of failure occurrences are discussed. The paper concludes with showing that the extended models fit into the structure of the differential equation presented at the beginning, which permits further interpretation.
结构覆盖增长和失效次数的向量马尔可夫模型
大多数软件可靠性增长模型将预期的失败次数指定为测试工作或日历时间的函数。然而,有一些方法来模拟驱动失效发生的中间因素的发展。本文首先提出了一个由四个连续关系组成的模型框架。结果表明,表示该框架的微分方程是几种有限失效范畴模型的推广。执行的测试用例的数量和预期的结构覆盖率之间的关系,以及预期的结构覆盖率和预期的失败发生的数量之间的关系,将被进一步探讨。提出了一种允许采样代码结构部分冗余的向量马尔可夫模型。该模型分别弥补了与操作测试和系统测试相关的设置之间的差距。讨论了考虑故障发生次数变化的部分冗余模型的两种扩展。本文最后表明,扩展模型符合开始时提出的微分方程的结构,这允许进一步解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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