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Reseach Article

Soft Computing Approaches for Prediction of Software Maintenance Effort

by Arvinder Kaur, Kamaldeep Kaur, Ruchika Malhotra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 16
Year of Publication: 2010
Authors: Arvinder Kaur, Kamaldeep Kaur, Ruchika Malhotra
10.5120/339-515

Arvinder Kaur, Kamaldeep Kaur, Ruchika Malhotra . Soft Computing Approaches for Prediction of Software Maintenance Effort. International Journal of Computer Applications. 1, 16 ( February 2010), 69-75. DOI=10.5120/339-515

@article{ 10.5120/339-515,
author = { Arvinder Kaur, Kamaldeep Kaur, Ruchika Malhotra },
title = { Soft Computing Approaches for Prediction of Software Maintenance Effort },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 16 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 69-75 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number16/339-515/ },
doi = { 10.5120/339-515 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:42:45.249800+05:30
%A Arvinder Kaur
%A Kamaldeep Kaur
%A Ruchika Malhotra
%T Soft Computing Approaches for Prediction of Software Maintenance Effort
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 16
%P 69-75
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The relationship between object oriented metrics and software maintenance effort is complex and non-linear. Therefore, there is considerable research interest in development and application of sophisticated techniques which can be used to construct models for predicting software maintenance effort. The aim of this paper is to evaluate and compare the application of different soft computing techniques - Artificial Neural Networks, Fuzzy Inference Systems and Adaptive Neuro-Fuzzy Inference Systems to construct models for prediction of Software Maintenance Effort. The maintenance effort data of two commercial software products is used in this study. The dependent variable in our study is maintenance effort. The independent variables are eight Object Oriented metrics . It is observed that soft computing techniques can be used for constructing accurate models for prediction of software maintenance effort and Adaptive Neuro Fuzzy Inference System technique gives the most accurate model.

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Index Terms

Computer Science
Information Sciences

Keywords

Software Maintenance Effort Prediction Soft Computing Object Oriented(OO) Metrics Artificial Neural Networks(ANNs) Fuzzy Inference Systems(FIS) Adaptive Neuro-Fuzzy Inference System(ANFIS)