A coupling-guided cluster analysis approach to reengineer the modularity of object-oriented systems

Describes a validation experiment of a quantitative approach to the modularization of object-oriented systems. The approach used is based on cluster analysis, a statistical technique used in many fields of science to group items. In this case, the clusters are modules and the items are classes. A sample of some relatively large object-oriented systems was used in this experiment. The calculation of the dissimilarity between classes is based on their relative couplings combined through six different rating schemes. These couplings are classified according to a taxonomy framework where categories were assigned weights. The coupling data were obtained with the MOODKit G2 tool. The results obtained allow conclusions concerning the applicability of the proposed approach. This work was developed in the realm of the MOOD (Modularization of Object-Oriented Systems) project, which aims to deliver a quantitative framework to support the design of object-oriented systems