Title: Prediction of Euclidean distance between existing and target product for software product line testing using FeatureIDE

Authors: Ashish Saini; Raj 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 ' Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management, Greater Noida, India ' INRIA, Nord Europe, CRISTAL, Lille, France

Abstract: Software product line (SPL) is a paradigm that consists a family of products, all these products have some common features. SPL contains enormous products due to variable features, to test all of them is unfeasible. For this reason, several methods have been introduced to test the product line. These methods are used to prioritise products because they are based on feature interaction and do not provide information regarding products' validity. To check the validity of products, we introduce a method based on Euclidean distance, which verifies the product based on the calculated distance between the real and desired product features. In addition, we compare the proposed method with the existing interaction-based method for product lines of different sizes. The results show that the proposed method takes less time to test the effectiveness of the product and increases the impact of the method in terms of time.

Keywords: software product line; SPL; feature model; software product line testing; testing; software product line engineering.

DOI: 10.1504/IJESMS.2021.10038986

International Journal of Engineering Systems Modelling and Simulation, 2021 Vol.12 No.4, pp.239 - 251

Received: 24 Dec 2020
Accepted: 18 Jan 2021

Published online: 22 Dec 2021 *

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