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Article type: Research Article
Authors: Yang, Yang-Rui* | Wang, He-Chuang | Xin, Yan-Hui
Affiliations: College of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, Henan 450000, China
Correspondence: [*] Corresponding author: Yang-Rui Yang, College of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou, Henan 450000, China. Tel./Fax: +86 013837176209; E-mail:[email protected]
Abstract: With the rapid development and the increasingly widespread application of information technology, the software becomes more and more important. Also, because of the increasing size and the complexity of software, the software quality has become difficult to control and manage. Improving the quality of software has become the focus of software industry. Software quality assurance becomes an important approach for improving software quality, which provides developers and managers with the information reflecting the product quality through monitoring the execution of software producing task by independent review. In this paper, we investigate the multiple attribute decision making (MADM) problems for evaluating the software quality with triangular fuzzy information. Then, we extend the grey relational analysis (GRA) procedure for triangular fuzzy multiple attribute decision making for evaluating marine service industry in triangular fuzzy setting. According to the concept of the GRA, a fuzzy relative relational degree is defined to determine the ranking order of all alternatives by calculating the degree of fuzzy grey relational coefficient to both the triangular fuzzy positive-ideal solution (TFPIS) and triangular fuzzy negative-ideal solution (TFNIS) simultaneously. Finally, an illustrative example for evaluating the software quality is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords: Multiple attribute decision-making (MADM), triangular fuzzy information, grey relational analysis (GRA), software quality
DOI: 10.3233/KES-170355
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 21, no. 2, pp. 97-102, 2017
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