NHPP SRGM效用的实证分析

W. Jiang, Ce Zhang, Wenyu Li, Miaomiao Fan, Zhichao Sun, Yafei Wen, Kaiwei Liu
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摘要

软件可靠性增长模型SRGM是软件测试阶段评估软件可靠性的有效工具。基于非均匀泊松过程NHPP的SRGM模型是应用最广泛的模型。到目前为止,该模型的有效范围尚不清楚。本文首先回顾了经典G-O模型的构建过程,总结了NHPP SRGM的建模过程,并简要分析了SRGM的研究内容和分类。为了验证许多nhpp型srgm在实际测试环境中的拟合和预测性能,本文使用26个srgm在19个真实数据集上进行了实验,并详细分析了11个不完善的调试模型在11个数据集上的性能。拟合曲线和拟合指标值,以及预测未来软件故障次数的预测曲线。实例验证结果表明,在任何测试环境下,模型都不可能具有优异的拟合和预测性能,即模型在应用环境下的性能存在差异性和不通用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Empirical Analysis of the Utility of NHPP SRGM
The software reliability growth model SRGM is an effective tool for evaluating software reliability in the software testing phase. The SRGM based on the non-homogeneous Poisson process NHPP is the most widely used model. So far, the validity range of the model has not been known. This article first reviews the construction process of the classic G-O model, summarizes the modeling process of NHPP SRGM, and briefly analyzes the research content and classification of SRGM. In order to verify the fitting and prediction performance of many NHPP-type SRGMs in the actual test environment, this paper uses 26 SRGMs to conduct experiments on 19 real data sets, and analyzes in detail the performance of 11 imperfect debugging models on 11 data sets. Fitting curve and fitting index value, as well as the prediction curve for predicting the number of failures of the software in the future. The results of the example verification show that no model can have excellent fitting and prediction performance in any test environment, that is, the performance of the model in the application environment is different and not universal.
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