An automated approach for noise identification to assist software architecture recovery techniques
We propose an automated methodology for noise detection. We assist SAR approaches to identify classes that obscure the system structure. We do not require a user defined threshold for noise detection. Our approach performs well in both complex and modularized designs. The tool implementing the proposed approach is freely available for download.
noise identification software architecture recovery omnipresent classes