A fuzzy rule-based approach for test case selection probability estimation in regression testing
by Leena Singh; Shailendra Narayan Singh; Sudhir Dawra; Renu Tuli
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 11, No. 3, 2019

Abstract: Regression testing is a very essential activity during maintenance of software. Due to constraints of time and cost, it is not possible to re-execute every test case with respect to every change occurred. Thus, a technique is required that selects and prioritises the test cases efficiently. This paper proposes a novel fuzzy rule-based approach for selecting and ordering a number of test cases from an existing test suite to predict the selection probability of test cases using multiple factors. The test cases, which have ability to find high fault detection rate with maximum coverage and minimum execution time to test are selected. The results specify the effectiveness of the proposed model for predicting the selection probability of individual test cases.

Online publication date: Mon, 29-Apr-2019

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 Aided Engineering and Technology (IJCAET):
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