Measuring Reliability of Aspect-Oriented Software Using a Combination of Artificial Neural Network and Imperialist Competitive Algorithm

Mohammad Zavvar, Shole Garavand, Mohammad Reza Nehi, Amangaldi Yanpi, Meysam Rezaei, Mohammad Hossein Zavvar
dx.doi.org/10.17576/apjitm-2016-0502-06

Abstract

Aspect-Oriented Software Engineering provides new ways to produce and deliver products and ultimately leads to reliable software. Reliability is an extremely important issue contributing to the quality of software. Thus, software engineers need proven mechanisms to determine the extent of software reliability. In this paper, a method for assessing reliability is proposed which takes advantage of a multilayer perceptron neural network. Furthermore, an imperialist competitive algorithm is used to optimize the weights to improve network performance. Finally, relying on root square mean error, the proposed approach is compared to a hybrid neural network-genetic algorithm method. The results show that the proposed approach exhibits lower error.

keyword

Aspect-Oriented Software; Artificial neural networks; Software reliability; Optimization; Algorithms

Area

Software Engineering and Technology