Title: Adapted rank order clustering-based test case prioritization for software product line testing

Authors: Satendra Kumar; Raj Kumar; Ashish Saini; Monika Rani

Addresses: Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar – 249404, India ' Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar – 249404, India ' Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar – 249404, India ' Department of Information Technology, Indian Institute of Information Technology Allahabad, Allahabad – 211012, India

Abstract: Software product line testing (SPLT) is a strenuous task due to the explosion of derivable products. It is infeasible to test all the products of a software product line (SPL), so several contributions have been presented to overcome this issue by reducing the number of products. However, not much consideration has been given to the test order of the products. Test case prioritization (TCP) technique arranges the test cases in a sequence to meet a specific performance goal. TCP is required to increase the effectiveness and efficiency of fault detection. In SPL, TCP technique arranges the configurations of products in order to be tested. Adapted rank order clustering (AROC)-based TCP approach is proposed for SPLT. Our AROC method utilises Binary Weight and Decimal Weight to arrange the products of an SPL. The results of the rigorous experimentation using AROC-based TCP approach are better than the random order and similarity-based order in terms of fault detection rate.

Keywords: SPLT; software product line testing; TCP; test case prioritization; rank order clustering; feature model.

DOI: 10.1504/IJAIP.2024.142665

International Journal of Advanced Intelligence Paradigms, 2024 Vol.29 No.2/3, pp.150 - 169

Received: 28 Mar 2019
Accepted: 19 Jun 2019
Published online: 15 Nov 2024 *

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