Improving software performance by automatic test cases through genetic algorithm
by Sudeshna Chakraborty; Vijay Bhanudas Gujar; Tanupriya Choudhury; Bhupesh Kumar Dewangan
International Journal of Computer Applications in Technology (IJCAT), Vol. 68, No. 3, 2022

Abstract: Software testing is a vital part of software development. One would like to decrease work and get the most out of the number of faults detected. For optimisation problems, test case production is used. Program checking for major problems in regular production trials has a known sufficiency importance factor. Generating test cases automatically will decrease the price and working time considerably. Experiment case information produced without any human interface by using genetic algorithm and random testing is compared with genetic algorithms. Observation is random testing limitations are solved by genetic algorithms. We have implemented these test cases and tested them in real time environments, and the outcomes show good performance.

Online publication date: Thu, 18-Aug-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com