Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/2076
Title: Software Product Line Regression Testing Based on Fuzzy Clustering Approach Using Distance Method
Authors: Saini, Ashish
Kumar, Raj
Kumar, Gaurav
Kumar, Satendra
Mittal, Mohit
Keywords: Product line
Software product line testing
Fuzzy C-means
FCM
Feature model
Testing
Software industries
Issue Date: 19-Oct-2022
Publisher: International Journal of Engineering Systems Modelling and Simulation
Citation: Vol.13, No.4; pp. 241-254
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.
URI: https://dx.doi.org/10.1504/IJESMS.2022.126301
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2076
ISSN: 1755-9766
1755-9758
Appears in Collections:Journal Articles

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