Managing the evolution of an OO system constitutes a complex and resource-consuming task. This is particularly true for reusable class libraries since the user interface must be preserved for version compatibility. Thus, the symptomatic detection of potential instabilities during the design phase of such libraries may help avoid later problems. This paper introduces a fuzzy logic-based approach for evaluating the stability of a reusable class library interface, using structural metrics as stability indicators. To evaluate this new approach, we conducted a preliminary study on a set of commercial C++ class libraries. The obtained results are very promising when compared to those of two classical machine learning approaches, top down induction of decision trees and Bayesian classifiers.

Many sources agree that managing the evolution of an OO system constitutes a complex and resource-consuming task. This is particularly true for reusable class libraries, as the user interface must be preserved to allow for version compatibility. Thus, the symptomatic detection of potential instabilities during the design phase of such libraries may serve to avoid later problems. This paper presents a fuzzy logic-based approach for evaluating the interface stability of a reusable class library, by using structural metrics as stability indicators.