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Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing

by Dr. Arvinder Kaur, Divya Bhatt
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 27 - Number 10
Year of Publication: 2011
Authors: Dr. Arvinder Kaur, Divya Bhatt
10.5120/3336-4589

Dr. Arvinder Kaur, Divya Bhatt . Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing. International Journal of Computer Applications. 27, 10 ( August 2011), 27-34. DOI=10.5120/3336-4589

@article{ 10.5120/3336-4589,
author = { Dr. Arvinder Kaur, Divya Bhatt },
title = { Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing },
journal = { International Journal of Computer Applications },
issue_date = { August 2011 },
volume = { 27 },
number = { 10 },
month = { August },
year = { 2011 },
issn = { 0975-8887 },
pages = { 27-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume27/number10/3336-4589/ },
doi = { 10.5120/3336-4589 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:13:25.497924+05:30
%A Dr. Arvinder Kaur
%A Divya Bhatt
%T Particle Swarm Optimization with Cross-Over Operator for Prioritization in Regression Testing
%J International Journal of Computer Applications
%@ 0975-8887
%V 27
%N 10
%P 27-34
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software Testing is continuous process of development and maintenance in life of software. In maintenance phase, regression testing gets exercisedwith additional resources/time for performance. The prioritization of test cases helps to reduce the cost-time of regression testing. Hence, completing Regression Testing effectively and on schedule is challenge for software tester. In this research paper, the Particle Swarm Optimization (PSO) technology has been studied and used with the blend of Genetic Algorithm (GA) and the hybrid prioritized algorithm has been proposed. The Particle Swarm Optimization is an optimization algorithm based on heuristic search which can be used to solve time-constraint environment of Test Case Prioritization and the concept of Genetic Algorithm will further help in diversifying the solution within whole search space. For finding the effectiveness of hybrid prioritization algorithm: the efficiency %, saving %, reduction % and APFD/APCC has been calculated.

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Index Terms

Computer Science
Information Sciences

Keywords

Regression Testing Particle Swarm Optimization Genetic Algorithms

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