Flexible Discrete Software Reliability Growth Model for Distributed Environment Incorporating Two Types of Imperfect Debugging

S. Khatri, P. K. Kapur, P. Johri
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引用次数: 7

Abstract

In literature we have several software reliability growth models developed to monitor the reliability growth during the testing phase of the software development. These models typically use the calendar / execution time and hence are known as continuous time SRGM. However, very little seems to have been done in the literature to develop discrete SRGM. Discrete SRGM uses test cases in computer test runs as a unit of testing. Debugging process is usually imperfect because during testing all software faults are not completely removed as they are difficult to locate or new faults might be introduced. In real software development environment, the number of failures observed need not be same as the number of errors removed. If the number of failures observed is more than the number of faults removed then we have the case of imperfect debugging. Due to the complexity of the software system and the incomplete understanding of the software requirements, specifications and structure, the testing team may not be able to remove the fault perfectly on detection of the failure and the original fault may remain or get replaced by another fault. In this paper, we discuss a discrete software reliability growth model for distributed system considering imperfect debugging that faults are not always corrected/removed when they are detected and fault generation. The proposed model assumes that the software system consists of a finite number of reused and newly developed sub-systems. The reused sub-systems do not involve the effect of severity of the faults on the software reliability growth phenomenon because they stabilize over a period of time i.e. the growth is uniform whereas, the newly developed subsystem does involve. For newly developed component, it is assumed that removal process follows logistic growth curve due to the fact that learning of removal team grows as testing progresses. The fault removal phenomena for reused and newly developed sub-systems have been modeled separately and are summed to obtain the total fault removal phenomenon of the software system. The model has been validated on two software data sets and it is shown that the proposed model fairs comparatively better than the existing one.
考虑两种不完全调试的分布式环境下柔性离散软件可靠性增长模型
在文献中,我们开发了几个软件可靠性增长模型来监控软件开发测试阶段的可靠性增长。这些模型通常使用日历/执行时间,因此被称为连续时间SRGM。然而,文献中似乎很少有研究开发离散SRGM。离散SRGM使用计算机测试运行中的测试用例作为测试单元。调试过程通常是不完美的,因为在测试过程中,由于很难定位或可能引入新的故障,所有的软件故障都没有完全消除。在实际的软件开发环境中,观察到的失败数量不一定与删除的错误数量相同。如果观察到的故障数量多于删除的故障数量,那么我们就遇到了不完美调试的情况。由于软件系统的复杂性以及对软件需求、规范和结构的不完全了解,测试团队在检测到故障后,可能无法完美地排除故障,原有的故障可能会保留或被另一个故障所取代。本文讨论了分布式系统的离散软件可靠性增长模型,该模型考虑了不完全调试和故障产生的情况。提出的模型假设软件系统由有限数量的重用和新开发的子系统组成。重用的子系统不涉及故障严重程度对软件可靠性增长现象的影响,因为它们在一段时间内是稳定的,即增长是均匀的,而新开发的子系统则涉及。对于新开发的组件,假设移除过程遵循logistic增长曲线,因为移除团队的学习随着测试的进行而增长。分别对重用子系统和新开发子系统的故障排除现象进行建模,并对其进行求和,得到软件系统的总体故障排除现象。在两个软件数据集上对该模型进行了验证,结果表明该模型比现有模型具有较好的性能。
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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