Aspect-oriented Software Maintainability Assessment Using Adaptive Neuro Fuzzy Inference System (anfis)

Abstract

Aspect-oriented development is a relatively new approach that emphasizes dealing with crosscutting concerns. In aspect-oriented programming, concern networks and requirement networks are independent and can easily be added to or removed from a model of system; therefore maintenance and modifying in aspect-oriented system models are easier than object-oriented ones. Software maintenance is an important activity in software development and one of the most expensive activities. Also, its vagueness in prediction at early stage of development makes the process more complex. Researchers and developers are working on devising various techniques/ algorithms for better prediction. The aim of the paper is to show that ANFIS can more accurately predict maintainability as compared to other models such as Fuzzy Logic. For this we selected four metrics and used them for training, testing and validation.