A Bayesian belief network for assessing the likelihood of fault content | IEEE Conference Publication | IEEE Xplore

A Bayesian belief network for assessing the likelihood of fault content


Abstract:

To predict software quality, we must consider various factors because software development consists of various activities, which the software reliability growth model (SR...Show More

Abstract:

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.
Date of Conference: 17-20 November 2003
Date Added to IEEE Xplore: 08 December 2003
Print ISBN:0-7695-2007-3
Print ISSN: 1071-9458
Conference Location: Denver, CO, USA

References

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