摘要 : This paper exploits the 'relationship between functional-enhancement (FE) activity and the distribution of software defects' to develop a discriminant model that identifies high-risk program modules, 'FE activity' and 'defect data... 展开 This paper exploits the 'relationship between functional-enhancement (FE) activity and the distribution of software defects' to develop a discriminant model that identifies high-risk program modules, 'FE activity' and 'defect data captured during the FE of a commercial programming language processing utility' serve to fit and test the predictive quality of this model. The model misclassification rates demonstrate that FE information is sufficient for developing discriminant models identifying high-risk program modules. Consideration of the misclassified functions leads us to suggest that: (1) the level of routines in the calling hierarchy introduces variation in defect distribution; and (2) the impact of a defect indicates the risk that it presents. Thus consideration of defect impact can improve the discriminant results. 收起