Bibyan Ritu, Anand Sameer, Aggarwal Anu G, Kaur Gurjeet
Department of Operational Research, University of Delhi, New Delhi, India.
Shaheed Sukhdev College of Business Studies, University of Delhi, New Delhi, India.
MethodsX. 2023 Feb 15;10:102076. doi: 10.1016/j.mex.2023.102076. eCollection 2023.
In the past, various Software Reliability Growth Models (SRGMs) have been proposed using different parameters to improve software worthiness. Testing Coverage is one such parameter that has been studied in numerous models of software in the past and it has proved its influence on the reliability models. To sustain themselves in the market, software firms keep upgrading their software with new features or enhancements by rectifying previously reported faults. Also, there is an impact of the random effect on testing coverage during both the testing and operational phase. In this paper, we have proposed a Software reliability growth model based on testing coverage with random effect along with imperfect debugging. Later, the multi-release problem is presented for the proposed model. The proposed model is validated on the dataset from Tandem Computers. The results for each release of the models have been discussed based on the different performance criteria. The numerical results illustrate that models fit the failure data significantly.•The random effect in the testing coverage rate is handled using Stochastic Differential Equations (SDE).•Three testing coverage functions used are Exponential, Weibull, and S-shaped.•Four Releases of the software model has been presented.
过去，人们提出了各种软件可靠性增长模型（SRGM），使用不同参数来提高软件适用性。测试覆盖率就是这样一个参数，过去在众多软件模型中都有研究，并且已证明其对可靠性模型有影响。为了在市场中立足，软件公司会通过纠正先前报告的故障，不断用新功能或增强功能升级其软件。此外，在测试和运行阶段，随机效应都会对测试覆盖率产生影响。在本文中，我们提出了一种基于具有随机效应和不完全调试的测试覆盖率的软件可靠性增长模型。随后，针对所提出的模型给出了多版本问题。所提出的模型在来自Tandem Computers的数据集上进行了验证。基于不同的性能标准，讨论了模型每次发布的结果。数值结果表明模型与故障数据拟合良好。
• 使用随机微分方程（SDE）处理测试覆盖率中的随机效应。
• 使用的三个测试覆盖率函数分别是指数函数、威布尔函数和S形函数。
• 给出了软件模型的四个版本。
