Modeling and managing risk early in software development

The authors present an automated modeling technique which can be used as an alternative to regression techniques to improve the quality of the software development process. The modeling process will allow for the reliable detection of potential problem areas and for the interpretation of the cause of the problem so that the most appropriate remedial action can be taken. It is shown that it can be used to facilitate the identification and aid the interpretation of the significant trends which characterize high risk components in several Ada systems. The effectiveness of the technique is evaluated based on a comparison with logistic regression based models.<>