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


Authors

Hossein Momeni - Computer Engineering Department, Golestan University, Gorgan, Iran. Shiva Zahedian - Mazandaran University of Sciences and Technology, Mazandaran, Iran.


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.


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ISRP Style

Hossein Momeni, Shiva Zahedian, Aspect-oriented Software Maintainability Assessment Using Adaptive Neuro Fuzzy Inference System (anfis), Journal of Mathematics and Computer Science, 12 (2014), no. 3, 243 - 252

AMA Style

Momeni Hossein, Zahedian Shiva, Aspect-oriented Software Maintainability Assessment Using Adaptive Neuro Fuzzy Inference System (anfis). J Math Comput SCI-JM. (2014); 12(3):243 - 252

Chicago/Turabian Style

Momeni, Hossein, Zahedian, Shiva. "Aspect-oriented Software Maintainability Assessment Using Adaptive Neuro Fuzzy Inference System (anfis)." Journal of Mathematics and Computer Science, 12, no. 3 (2014): 243 - 252


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