Next Article in Journal
Some Inequalities Using Generalized Convex Functions in Quantum Analysis
Previous Article in Journal
Spacetime and Deformations of Special Relativistic Kinematics
Previous Article in Special Issue
A Rough Hybrid Multicriteria Decision-Making Model for Improving the Quality of a Research Information System
Open AccessArticle

Novel Fuzzy Clustering Methods for Test Case Prioritization in Software Projects

School of Computing, SASTRA University, Thanjavur 613401, TN, India
Department of Mathematics, National Institute of Technology, Durgapur, West Bengal 713209, India
Faculty of Economics and Management, University of Szczecin, Mickiewicza 64, 71-101 Szczecin, Poland
Department of Computer Science and Information Technology, West Pomeranian University of Technology, Zolnierska 49, 71-210 Szczecin, Poland
Author to whom correspondence should be addressed.
Symmetry 2019, 11(11), 1400;
Received: 9 August 2019 / Revised: 3 October 2019 / Accepted: 5 October 2019 / Published: 12 November 2019
(This article belongs to the Special Issue Multi-Criteria Decision Aid methods in fuzzy decision problems)
Systematic Regression Testing is essential for maintaining software quality, but the cost of regression testing is high. Test case prioritization (TCP) is a widely used approach to reduce this cost. Many researchers have proposed regression test case prioritization techniques, and clustering is one of the popular methods for prioritization. The task of selecting appropriate test cases and identifying faulty functions involves ambiguities and uncertainties. To alleviate the issue, in this paper, two fuzzy-based clustering techniques are proposed for TCP using newly derived similarity coefficient and dominancy measure. Proposed techniques adopt grouping technology for clustering and the Weighted Arithmetic Sum Product Assessment (WASPAS) method for ranking. Initially, test cases are clustered using similarity//dominancy measures, which are later prioritized using the WASPAS method under both inter- and intra-perspectives. The proposed algorithms are evaluated using real-time data obtained from Software-artifact Infrastructure Repository (SIR). On evaluation, it is inferred that the proposed algorithms increase the likelihood of selecting more relevant test cases when compared to the recent state-of-the-art techniques. Finally, the strengths of the proposed algorithms are discussed in comparison with state-of-the-art techniques. View Full-Text
Keywords: regression testing; test case prioritization; grouping technology; clustering; WASPAS regression testing; test case prioritization; grouping technology; clustering; WASPAS
Show Figures

Figure 1

MDPI and ACS Style

Shrivathsan, A.D.; Ravichandran, K.S.; Krishankumar, R.; Sangeetha, V.; Kar, S.; Ziemba, P.; Jankowski, J. Novel Fuzzy Clustering Methods for Test Case Prioritization in Software Projects. Symmetry 2019, 11, 1400.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop