Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Palak Palak
Maharshi Dayanand University
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Hybrid swarm and GA based approach for software test case selection Palak Palak; Preeti Gulia
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 6: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (298.374 KB) | DOI: 10.11591/ijece.v9i6.pp4898-4903

Abstract

Being a crucial step and deciding factor for software reliability, software testing has evolved a long way and always attracted researchers due to various inherent challenges. The quality of a software application depends on the effectiveness of the testing carried out during development and maintenance phase. Testing is a crucial but time consuming activity that influences the overall cost of software development. Thus a minimal but efficient test suite selection is the need of the hour. This paper presents a hybrid technique based on swarm based search technique and GA (Genetic Algorithm) for selection of promising test cases to reduce the overall development cost and time of the application. We took component based software into consideration as they offer some inherent advantages over traditional software development paradigms.
Hybrid swarm intelligence-based software testing techniques for improving quality of component based software Palak Palak; Preeti Gulia; Nasib Singh Gill
Indonesian Journal of Electrical Engineering and Computer Science Vol 22, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v22.i3.pp1716-1722

Abstract

Being a time-consuming and costly activity, software testing always demands optimization and automation. Software testing is an important activity to achieve quality and customer satisfaction. This paper presents a comparative evaluation of different hybrid automated software testing techniques using the concepts of soft computing for overall quality enhancement. A comparison between three hybrid automation techniques is carried out i.e., hybrid ant colony optimization-genetic algorithms (ACO-GA), hybrid artificial bee colony (ABC)-Naïve Bayes, hybrid ABC-GA along with three parent approaches. The comparison is made by applying these hybrid techniques for the selection of minimized test suites thus reducing overall testing effort and eliminating useless or redundant test cases. The experimental results prove the efficiency of these hybrid approaches in different scenarios. The impact of automated testing techniques for quality enhancement is assessed in terms of defect density and defect detection percentage.
Co-Authors Nasib Singh Gill Preeti Gulia