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基于改进G-O模型的软件可靠性测试方法

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为克服传统G-O(Goel-Okumoto)软件可靠性模型中缺陷发现率过于简化处理的局限性,提出了一种以更精准的方式描述缺陷发现率随时间实际变化的模型。改进模型不同于常规假设将其视为恒定或单调的函数,并考虑了测试人员的学习和排错能力的进步,以及软件固有的缺陷发现率随时间递减的趋势,从而假设缺陷发现率呈现先上升后下降的动态变化趋势。通过在两组公开的软件缺陷检测数据集上的应用,并与多种经典的模型进行了对比验证,验证了模型的有效性。实验结果表明,改进后的G-O模型在拟合能力和预测能力方面都显示出优异的性能,证明其在软件可靠性评估中的适用性和优越性。
Software Reliability Testing Method Based on Improved G-O Model
In order to overcome the oversimplified treatment of the defect discovery rate in the traditional G-O(Goel-Okumoto)software reliability model,an improved model that more accurately describes the actual change of the defect discovery rate over time is proposed.Unlike the conventional assumption that it is treated as a constant or monotonic function,the improved model considers the progress of testers'learning and debugging capabilities and the inherent tendency of the software's defect discovery rate to decrease over time.Therefore,it assumes that the defect discovery rate first increases before showing a dynamic trend of decline.The model's effectiveness is verified by applying it to two sets of public software defect detectionda tasets and comparing it with a variety of classic models.Experimental results confirm that the improved G-O model demonstrates excellent performance in both fitting and prediction capabilities,proving its applicability and superiority in software reliability assessment.

softwarereliability modeldefect discovery rateGoel-Okumoto(G-O)modelparameter estimation

刘早、高钦旭、邓阿北、辛士界、于彪

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吉林省电子信息产品检验研究院软件评测中心,长春 130021

吉林大学计算机科学与技术学院,长春 130012

软件可靠性模型 缺陷发现率 G-O模型 参数估计

吉林省科技发展计划基金资助项目

20230201082GX

2024

吉林大学学报(信息科学版)
吉林大学

吉林大学学报(信息科学版)

CSTPCD
影响因子:0.607
ISSN:1671-5896
年,卷(期):2024.42(5)