A Bayesian belief network for assessing the likelihood of fault content
A Bayesian belief network for assessing the likelihood of fault content
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DOI：
10.1109/issre.2003.1251044
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发表时间：
2003-11
期刊：
影响因子：
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通讯作者：
S. Amasaki;Yasunari Takagi;O. Mizuno;T. Kikuno
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文献类型：
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作者：
S. Amasaki;Yasunari Takagi;O. Mizuno;T. Kikuno
为了预测软件质量，我们必须考虑各种因素，因为软件开发由各种活动组成，而软件可靠性增长模型(SRGM)没有考虑这一点。本文提出了一种基于贝叶斯信任网络(BBN)的软件产品最终质量预测模型。通过使用BBN，我们可以构建一个预测模型，该模型关注于软件开发过程的结构，显式地表示度量之间的复杂关系，并处理不确定的度量，如软件产品中的残留故障。为了对所构建的模型进行评估，我们基于从某公司开发项目中收集的度量数据进行了实证实验。实证结果表明，该模型能够预测SRGM不能处理的剩余故障数量。
To predict software quality, we must consider various factors because software development consists of various activities, which the software reliability growth model (SRGM) does not consider. In this paper, we propose a model to predict the final quality of a software product by using the Bayesian belief network (BBN) model. By using the BBN, we can construct a prediction model that focuses on the structure of the software development process explicitly representing complex relationships between metrics, and handling uncertain metrics, such as residual faults in the software products. In order to evaluate the constructed model, we perform an empirical experiment based on the metrics data collected from development projects in a certain company. As a result of the empirical evaluation, we confirm that the proposed model can predict the amount of residual faults that the SRGM cannot handle.