Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm

Aspect-oriented software engineering provides new ways to produce and deliver products and ultimately leads to reliable software. Reliability is an important issue contributing to the quality of software. Thus, software engineers need proven mechanisms to determine the extent of software reliability...

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Main Authors:	Zavvar, Mohammad, Garavand, Shole, Nehi, Mohammad Reza, Yanpi, Amangaldi, Rezaei, Meysam, Zavvar, Mohammad Hossein
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2016
Online Access:	http://journalarticle.ukm.my/10064/ http://journalarticle.ukm.my/10064/ http://journalarticle.ukm.my/10064/1/15265-46490-1-PB.pdf

id	ukm-10064
recordtype	eprints
spelling	ukm-100642017-02-01T06:42:20Z http://journalarticle.ukm.my/10064/ Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm Zavvar, Mohammad Garavand, Shole Nehi, Mohammad Reza Yanpi, Amangaldi Rezaei, Meysam Zavvar, Mohammad Hossein Aspect-oriented software engineering provides new ways to produce and deliver products and ultimately leads to reliable software. Reliability is an 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 measuring reliability is proposed which takes advantage of a Multilayer Perceptron Artificial Neural Network (MLPANN). Furthermore, an Imperialist Competitive Algorithm (ICA) is used to optimize the weights to improve network performance. Finally, relying on Root Mean Square Error (RMSE), the proposed approach is compared to a hybrid Genetic Algorithm- Artificial Neural Network (GA-ANN) method. The results show that the proposed approach exhibits lower error. Penerbit Universiti Kebangsaan Malaysia 2016-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/10064/1/15265-46490-1-PB.pdf Zavvar, Mohammad and Garavand, Shole and Nehi, Mohammad Reza and Yanpi, Amangaldi and Rezaei, Meysam and Zavvar, Mohammad Hossein (2016) Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm. Asia-Pacific Journal of Information Technology and Multimedia, 5 (2). pp. 75-84. ISSN 2289-2192 http://ejournals.ukm.my/apjitm/issue/view/871
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Aspect-oriented software engineering provides new ways to produce and deliver products and ultimately leads to reliable software. Reliability is an 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 measuring reliability is proposed which takes advantage of a Multilayer Perceptron Artificial Neural Network (MLPANN). Furthermore, an Imperialist Competitive Algorithm (ICA) is used to optimize the weights to improve network performance. Finally, relying on Root Mean Square Error (RMSE), the proposed approach is compared to a hybrid Genetic Algorithm- Artificial Neural Network (GA-ANN) method. The results show that the proposed approach exhibits lower error.
format	Article
author	Zavvar, Mohammad Garavand, Shole Nehi, Mohammad Reza Yanpi, Amangaldi Rezaei, Meysam Zavvar, Mohammad Hossein
spellingShingle	Zavvar, Mohammad Garavand, Shole Nehi, Mohammad Reza Yanpi, Amangaldi Rezaei, Meysam Zavvar, Mohammad Hossein Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
author_facet	Zavvar, Mohammad Garavand, Shole Nehi, Mohammad Reza Yanpi, Amangaldi Rezaei, Meysam Zavvar, Mohammad Hossein
author_sort	Zavvar, Mohammad
title	Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
title_short	Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
title_full	Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
title_fullStr	Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
title_full_unstemmed	Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
title_sort	measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2016
url	http://journalarticle.ukm.my/10064/ http://journalarticle.ukm.my/10064/ http://journalarticle.ukm.my/10064/1/15265-46490-1-PB.pdf
first_indexed	2023-09-18T19:56:24Z
last_indexed	2023-09-18T19:56:24Z
_version_	1777406558088462336

Measuring reliability of aspect-oriented software using a combination of artificial neural network and imperialist competitive algorithm

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