Modeling the Role of Testing Coverage in the Software Reliability Assessment

Sudeep Kumar, A. Aggarwal, Ritu Gupta
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Abstract

To assure the reliability and quality of the final product, testing is an essential and crucial part in the software development cycle. During this process, fault correction/detection activities are carried out to increase the reliability of the software. The non-homogeneous Poisson Process (NHPP) is the basis of the investigated software reliability growth models (SRGMs), which are based on the supposition that the number of faults found is affected by the amount of code covered during testing and that the amount of code covered during testing depends on the testing effort expended. This research takes into consideration several testing coverage functions: exponential, delayed S-shaped and logistic distributions, to propose three SRGMs that are based on testing efforts. For testing effort expenditure Weibull distribution has been employed. Two real failure datasets have been utilised to validate the proposed models, and their performance is evaluated using four goodness-of-fit metrics, including predictive ratio risk (PRR), coefficient of determination (R^2 ), predictive power (PP) and mean square error (MSE). Sensitivity analysis of cost requirement-based release time of software for exponential function has been done by using a genetic algorithm, which minimized the overall cost of the software subject to the requirement for reliability.
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测试覆盖率在软件可靠性评估中的作用建模
为了确保最终产品的可靠性和质量,测试是软件开发周期中必不可少的关键部分。在此过程中,进行故障校正/检测活动以提高软件的可靠性。非齐次泊松过程(NHPP)是所研究的软件可靠性增长模型(SRGM)的基础,该模型基于这样一种假设,即发现的故障数量受测试期间覆盖的代码数量的影响,并且测试期间涵盖的代码数量取决于所花费的测试工作量。本研究考虑了几个测试覆盖函数:指数分布、延迟S形分布和逻辑分布,提出了三个基于测试工作的SRGM。为了测试工作量,采用了威布尔分布。使用两个实际故障数据集来验证所提出的模型,并使用四个拟合优度指标来评估其性能,包括预测比率风险(PRR)、决定系数(R^2)、预测能力(PP)和均方误差(MSE)。利用遗传算法对指数函数软件基于成本需求的发布时间进行了敏感性分析,使软件的总体成本在满足可靠性要求的前提下最小化。
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来源期刊
CiteScore
3.80
自引率
6.20%
发文量
57
审稿时长
20 weeks
期刊介绍: IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.
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