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Software reliability models with time-dependent hazard function based on Bayesian approach

机译:基于贝叶斯方法的具有时变危险函数的软件可靠性模型

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In this paper, two models predicting mean time until next failure based on Bayesian approach are presented. Times between failures follow Weibull distributions with stochastically decreasing ordering on the hazard functions of successive failure time intervals, reflecting the tester's intent to improve the software quality with each corrective action. We apply the proposed models to actual software failure data and show they give better results under sum of square errors criteria as compared to previous Bayesian models and other existing times between failures models. Finally, we utilize likelihood ratios criterion to compare new model's predictive performance.
机译:在本文中,提出了两种基于贝叶斯方法预测下一次失效的平均时间的模型。故障之间的时间遵循Weibull分布,并在连续故障时间间隔的危害函数上以随机递减的顺序排列,这反映了测试人员通过每次纠正措施来改善软件质量的意图。我们将建议的模型应用于实际的软件故障数据,并显示与以前的贝叶斯模型以及故障模型之间的其他现有时间相比,在平方误差和标准下,它们可以提供更好的结果。最后,我们利用似然比准则比较新模型的预测性能。

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