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Defect Analysis and Prediction by Applying the Multistage Software Reliability Growth Model

机译:应用多阶段软件可靠性增长模型进行缺陷分析和预测

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摘要

In software development, defects are inevitable. To improve reliability, software reliability growth models are useful to analyze projects. Selecting an expedient model can also help with defect predictions, but the model must be well fitted to all the original data. A particular software reliability growth model may not fit all the data well. To overcome this issue, herein we use multistage modeling to fit defect data. In the multistage model, an evaluation is used to divide the data into several parts. Each part is fitted with its own growth model, and the separate models are recombined. As a case study, projects provided by a Japanese enterprise are analyzed by both traditional software reliability growth models and the multistage model. The multistage model has a better performance for data with a poor fit using a traditional software reliability growth model.
机译:在软件开发中,缺陷是不可避免的。为了提高可靠性,软件可靠性增长模型可用于分析项目。选择权宜的模型也可以帮助进行缺陷预测,但是该模型必须很好地适合所有原始数据。特定的软件可靠性增长模型可能无法很好地拟合所有数据。为了克服这个问题,本文中我们使用多阶段建模来拟合缺陷数据。在多阶段模型中,使用评估将数据分为几个部分。每个部分都具有自己的增长模型,并且重新组合了单独的模型。作为案例研究,日本企业提供的项目将通过传统的软件可靠性增长模型和多阶段模型进行分析。使用传统的软件可靠性增长模型,多阶段模型对于拟合度较差的数据具有更好的性能。

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