Software Reliability Engineering: A Roadmap
FOSE '07 2007 Future of Software Engineering
Quantitative analysis of faults and failures with multiple releases of softpm
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
A Bayesian model for predicting reliability of software systems at the architectural level
QoSA'07 Proceedings of the Quality of software architectures 3rd international conference on Software architectures, components, and applications
Dependability metrics
Prediction of defect distribution based on project characteristics for proactive project management
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Evaluating simulation software components with player rating systems
Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques
Software defect prediction using Bayesian networks
Empirical Software Engineering
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To predict software quality, we must consider variousfactors because software development consists of variousactivities, which the software reliability growth model(SRGM) does not consider.In this paper, we propose a model to predict the finalquality of a software product by using the Bayesian beliefnetwork (BBN) model. By using the BBN, we can constructa prediction model that focuses on the structure of the softwaredevelopment process explicitly representing complexrelationships between metrics, and handling uncertain metrics,such as residual faults in the software products. Inorder to evaluate the constructed model, we perform anempirical experiment based on the metrics data collectedfrom development projects in a certain company. As a resultof the empirical evaluation, we confirm that the proposedmodel can predict the amount of residual faults thatthe SRGM cannot handle.