Software reliability modeling and prediction are important issues during software development, especially when one has to reach a desired reliability prior to software release. Various techniques, both static and dyna...Software reliability modeling and prediction are important issues during software development, especially when one has to reach a desired reliability prior to software release. Various techniques, both static and dynamic, are used for reliability modeling and prediction in the context of software risk management. The single-phase Rayleigh model is a dynamic reliability model;however, it is not suitable for software release date prediction. We propose a new multi-phase truncated Rayleigh model and obtain parameter estimation using the nonlinear least squares method. The proposed model has been successfully tested in a large software company for several software projects. It is shown that the two-phase truncated Rayleigh model outperforms the traditional single-phase Rayleigh model in modeling weekly software defect arrival data. The model is useful for project management in planning release times and defect management.展开更多
文摘Software reliability modeling and prediction are important issues during software development, especially when one has to reach a desired reliability prior to software release. Various techniques, both static and dynamic, are used for reliability modeling and prediction in the context of software risk management. The single-phase Rayleigh model is a dynamic reliability model;however, it is not suitable for software release date prediction. We propose a new multi-phase truncated Rayleigh model and obtain parameter estimation using the nonlinear least squares method. The proposed model has been successfully tested in a large software company for several software projects. It is shown that the two-phase truncated Rayleigh model outperforms the traditional single-phase Rayleigh model in modeling weekly software defect arrival data. The model is useful for project management in planning release times and defect management.
