Paper Info
Title
An Effective Regression Test Case Selection Using Hybrid Whale Optimization Algorithm
Abstract
AbstractTest suite optimization is an ever-demanded approach for regression test cost reduction. Regression testing is conducted to identify any adverse effects of maintenance activity on previously working versions of the software. It consumes almost seventy percent of the overall software development lifecycle budget. Regression test cost reduction is therefore of vital importance. Test suite optimization is the most explored approach to reduce the test suite size to re-execute. This article focuses on test suite optimization as a regression test case selection, which is a proven N-P hard combinatorial optimization problem. The authors have proposed an almost safe regression test case selection approach using a Hybrid Whale Optimization Algorithm and empirically evaluated the same on subject programs retrieved from the Software Artifact Infrastructure Repository with Bat Search and ACO-based regression test case selection approaches. The analyses of the obtained results indicate an improvement in the fault detection ability of the proposed approach over the compared ones with significant reduction in test suite size.
Year
DOI
Venue
2020
10.4018/IJDST.2020010105
Periodicals
Keywords
Field
DocType
Hybrid Whale Optimization Algorithm, Nature Inspired Meta-Heuristics, Regression Testing, Software Maintenance, Test Case Selection, Test Suite Optimization
Whale,Data mining,Computer science,Regression testing,Real-time computing,Optimization algorithm
Journal
Volume
Issue
ISSN
11
1
1947-3532
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Arun Prakash Agrawal181.81
Ankur Choudhary232.43
Arvinder Kaur337026.99