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A Bayesian belief network for assessing the likelihood of fault content

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4 Author(s)
Amasaki, S. ; Graduate Sch. of Inf. Sci. & Technol., Osaka Univ., Japan ; Takagi, Y. ; Mizuno, O. ; Kikuno, T.

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.

Published in:

Software Reliability Engineering, 2003. ISSRE 2003. 14th International Symposium on

Date of Conference:

17-20 Nov. 2003