Title: A fuzzy rule-based approach for test case selection probability estimation in regression testing

Authors: Leena Singh; Shailendra Narayan Singh; Sudhir Dawra; Renu Tuli

Addresses: ASET, Amity University, Uttar Pradesh, Noida, India ' ASET, Amity University, Uttar Pradesh, Noida, India ' Tecnia Institute of Advanced Studies, New Delhi, India ' Amity School of Engineering and Technology, New Delhi, India

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.

Keywords: prioritisation; regression testing; selection probability; fuzzy rule.

DOI: 10.1504/IJCAET.2019.099336

International Journal of Computer Aided Engineering and Technology, 2019 Vol.11 No.3, pp.391 - 408

Received: 09 Nov 2016
Accepted: 03 May 2017

Published online: 29 Apr 2019 *

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