Small Sample Fault Data Prediction Study Based on Weibull Model

Hongpo Wang, Ge Yang, Linnan Bai, Juan Yin, Qiang Li
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引用次数: 3

Abstract

Using software testing data collected, this paper established a software safety defects S curve model based on Weibull model theory. χ2 testing and prediction error testing are employed to verify the matching ability of the Weibull model and applicability of the predicting result. How to select truncation error is also discussed here. Results show that better predictive effect can be achieved if computational formula of truncation error is properly adjusted. The application of predicting model was also developed in this paper. Small sample fault data prediction and predicting error problems are discussed here. If the amount of fault data accumulated is not big enough, prediction cannot carry out. Analyzing results point out that it can be solved through the combination of different types of data. Then variation tendency of small sample fault data can be predicted.
基于威布尔模型的小样本故障预测研究
本文利用收集到的软件测试数据,基于威布尔模型理论建立了软件安全缺陷S曲线模型。采用χ2检验和预测误差检验验证威布尔模型的匹配能力和预测结果的适用性。本文还讨论了如何选择截断误差。结果表明,适当调整截断误差的计算公式,可以取得较好的预测效果。本文还对预测模型的应用进行了探讨。讨论了小样本故障数据预测和预测误差问题。如果累积的故障数据量不够大,则无法进行预测。分析结果表明,可以通过不同类型数据的组合来解决。进而预测小样本故障数据的变化趋势。
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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