A metric based technique for design flaws detection and correction

During the evolution of object-oriented (OO) systems, the preservation of correct design should be a permanent quest. However, for systems involving a large number of classes and which are subject to frequent modifications, the detection and correction of design flaws may be a complex and resource-consuming task. Automating the detection and correction of design flaws is a good solution to this problem. Various authors have proposed transformations that improve the quality of an OO system while preserving its behavior. In this paper, we propose a technique for automatically detecting situations where a particular transformation can be applied to improve the quality of a system. The detection process is based on analyzing the impact of various transformations on software metrics using quality estimation models