Classes are apt to include useless codes and inadequate inheritance relationship between them when they are being updated, inserted and deleted during the evolution process of object-oriented software, leading to lots of errors. Conventional class restructuring methods degrade the effectiveness of reusability since they go with preprocesses such as dependency analysis and estimation of class cohesion and run statically. In this paper, we propose a new C＋＋ class-restructuring algorithm that does not require those preprocesses and runs dynamically by improving ART learning algorithm in the artificial neural networks.