Multicriteria Cuckoo search optimized latent Dirichlet allocation based Ruzchika indexive regression for software quality management

The paper presents the software quality management is a highly significant one to ensure the quality and to review the reliability of software products. To improve the software quality by predicting software failures and enhancing the scalability, in this paper, we present a novel reinforced Cuckoo...

Full description

Saved in:
Bibliographic Details
Main Authors: Chennappan, R. (Author), Thulasiraman, Vidyaa (Author)
Format: EJournal Article
Published: Institute of Advanced Engineering and Science, 2021-12-01.
Subjects:
Online Access:Get fulltext
Tags: Add Tag
No Tags, Be the first to tag this record!
LEADER 02818 am a22003013u 4500
001 ijeecs26336_15834
042 |a dc 
100 1 0 |a Chennappan, R.  |e author 
100 1 0 |e contributor 
700 1 0 |a Thulasiraman, Vidyaa  |e author 
245 0 0 |a Multicriteria Cuckoo search optimized latent Dirichlet allocation based Ruzchika indexive regression for software quality management 
260 |b Institute of Advanced Engineering and Science,   |c 2021-12-01. 
500 |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/26336 
520 |a The paper presents the software quality management is a highly significant one to ensure the quality and to review the reliability of software products. To improve the software quality by predicting software failures and enhancing the scalability, in this paper, we present a novel reinforced Cuckoo search optimized latent Dirichlet allocation based Ruzchika indexive regression (RCSOLDA-RIR) technique. At first, Multicriteria reinforced Cuckoo search optimization is used to perform the test case selection and find the most optimal solution while considering the multiple criteria and selecting the optimal test cases for testing the software quality. Next, the generative latent Dirichlet allocation model is applied to predict the software failure density with selected optimal test cases with minimum time. Finally, the Ruzchika indexive regression is applied for measuring the similarity between the preceding versions and the new version of software products. Based on the similarity estimation, the software failure density of the new version is also predicted. With this, software error prediction is made in a significant manner, therefore, improving the reliability of software code and service provisioning time between software versions in software systems is also minimized. An experimental assessment of the RCSOLDA-RIR technique achieves better reliability and scalability than the existing methods. 
540 |a Copyright (c) 2021 Institute of Advanced Engineering and Science 
540 |a http://creativecommons.org/licenses/by-nc/4.0 
546 |a eng 
690
690 |a Generative latent dirichlet allocation model; Multicriteria reinforced cuckoo search optimization; Ruzchika indexive regression; Software quality management; 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 24, No 3: December 2021; 1804-1813 
786 0 |n 2502-4760 
786 0 |n 2502-4752 
786 0 |n 10.11591/ijeecs.v24.i3 
787 0 |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/26336/15834 
856 4 1 |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/26336/15834  |z Get fulltext