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Study of Test Case Selection and Prioritization

by Kevilienuo Kire, Neha Malhotra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 5
Year of Publication: 2014
Authors: Kevilienuo Kire, Neha Malhotra
10.5120/14838-3100

Kevilienuo Kire, Neha Malhotra . Study of Test Case Selection and Prioritization. International Journal of Computer Applications. 85, 5 ( January 2014), 28-30. DOI=10.5120/14838-3100

@article{ 10.5120/14838-3100,
author = { Kevilienuo Kire, Neha Malhotra },
title = { Study of Test Case Selection and Prioritization },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 5 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 28-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number5/14838-3100/ },
doi = { 10.5120/14838-3100 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:01:40.675483+05:30
%A Kevilienuo Kire
%A Neha Malhotra
%T Study of Test Case Selection and Prioritization
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 5
%P 28-30
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software testing is very important for ensuring software quality in organizations. In fact, the quality of test suite plays an important role for the success of software testing . Ant colony optimization (ACO) which is a part of Swarm Intelligence is used to settle optimization problem. This paper attempts to provide ideas of Test Case Selection and Prioritization which Ant Colony Optimization which can be helpful for the researchers who are working on software testing. There is a great expectation in the field of Swarm Intelligence as it always comes with a challenging thought. ACO is one of such promising approaches for its application in Software Testing.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Ant Colony Optimization Coverage Genetic algorithms Simulated Annealing Algorithms Pheromone Table Regression Testing Test Case Prioritization Test Case Selection.

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