Design Pattern Recognition by Using Adaptive Neuro Fuzzy Inference System

Abstract

Software design patterns describe recurring design problems and provide the essence of best practice solutions. It is useful and important, for various software engineering tasks, to know which design pattern is implemented where in a software design. However, this information is often lost due to poor or absent documentation, and so accurate recognition tools are required. The problem is that design patterns, given their abstract and vague nature, have a level of resistance to be automatically and accurately recognized. Although this vagueness or fuzziness can be captured and modelled by the fuzzy inference system, it has not yet been applied to solve this problem. This paper fills this gap by proposing an approach for design pattern recognition based on Adaptive Neuro Fuzzy Inference System. Our approach consists of two phases: space reduction phase and design pattern recognition phase. Both phases are implemented by ANFIS. We evaluate the approach by an experiment conducted to recognize six design patterns in an open source application. The results show that the approach is viable and promising.