Title: Software product line regression testing based on fuzzy clustering approach using distance method

Authors: Ashish Saini; Raj Kumar; Gaurav Kumar; Satendra Kumar; Mohit Mittal

Addresses: Department of Computer Science, Gurukula Kangri (Deemed to be University), Haridwar, India ' Department of Computer Science, Gurukula Kangri (Deemed to be University), Haridwar, India ' College of Engineering and Design, Alliance University, Bengaluru, India ' Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management, Greater Noida, India ' INRIA, Nord Europe, CRISTAL, Lille, France

Abstract: Testing is a process that takes much time and effort in software companies. This becomes even more difficult and boring when it comes to testing a software product line (SPL). The SPL is a model in which multiple products from the same family are made simultaneously. Testing of all products is not possible. Hence a lot of testing methods have been given from time to time to test the product line, given by researchers based on contemporary conception. In the direction of testing product lines, this article has proposed a method, which used fuzzy C-means clustering with the Jaro-Winkler distance method. Variable features of the product form the basis for cluster development. The proposed method is compared with other distance methodologies. After comparison, it is concluded that the proposed method provides better results than other methods. This article has resorted to some product lines to compare with the proposed methods.

Keywords: product line; software product line testing; fuzzy C-means; FCM; feature model; testing; software industries.

DOI: 10.1504/IJESMS.2022.126301

International Journal of Engineering Systems Modelling and Simulation, 2022 Vol.13 No.4, pp.241 - 254

Received: 23 Jun 2021
Accepted: 16 Aug 2021
Published online: 19 Oct 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article