Software product line regression testing based on fuzzy clustering approach using distance method. (5th September 2022)

• Record Type: Journal Article
• Authors: Saini, Ashish; Kumar, Raj; Kumar, Gaurav; Kumar, Satendra; Mittal, Mohit
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 13:Number 4(2022)
• Page Start: 241
• Page End: 254
• Publication Date: 2022-09-05
• Subjects: product line -- software product line testing -- fuzzy C-means -- FCM -- feature model -- testing -- software industries; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

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.