Object oriented software quality prediction using general regression neural networks
ACM SIGSOFT Software Engineering Notes
An empirical analysis of a testability model for object-oriented programs
ACM SIGSOFT Software Engineering Notes
Evaluating the effect of control flow on the unit testing effort of classes: an empirical analysis
Advances in Software Engineering
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We model the relationship between static software product measures and a dynamic quality measure, testability. To our knowledge, this is the first time a dynamic quality measure has been modeled using static software product measures. We first give an overview of testability analysis and discriminant modeling. Using static software product measures collected from a real time avionics software system, we develop two discriminant models and classify the component program modules as having low or high testability. The independent variables are principal components derived from the observed software product measures. One model is used to evaluate the quality of fit and one is used to assess classification performance. We show that for this study, the quality of fit and classification performance of the discriminant modeling methodology are excellent and yield a potentially useful insight into the relationship between static software measures and testability.