Compensation model of multi-attribute decision making and its application to N-version software choice
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URI (for links/citations):
https://link.springer.com/chapter/10.1007%2F978-3-319-57141-6_16https://elib.sfu-kras.ru/handle/2311/70269
Author:
Gruzenkin, D. V.
Grishina, G. V.
Durmuş, M. S.
Üstoǧlu, İ.
Tsarev, R. Yu.
Corporate Contributor:
Институт космических и информационных технологий
Институт филологии и языковой коммуникации
Кафедра информатики
Кафедра иностранных языков для инженерных направлений
Date:
2017-04Journal Name:
Advances in Intelligent Systems and ComputingJournal Quartile in Scopus:
Q4Journal Quartile in Web of Science:
без квартиляBibliographic Citation:
Gruzenkin, D. V. Compensation model of multi-attribute decision making and its application to N-version software choice [Текст] / D. V. Gruzenkin, G. V. Grishina, M. S. Durmuş, İ. Üstoǧlu, R. Yu. Tsarev // Advances in Intelligent Systems and Computing. — 2017. — Т. 575. — С. 148-157Abstract:
Multi-attribute decision making deals with discrete finite set of alternatives. The solution to the multi-attribute decision making problem is the choice of an alternative from the set of all possible alternatives on the base of usually contradicting attributes. In this paper, a new multi-attribute decision making model is presented. The proposed model develops a linear compensatory process for the interconnected attributes. It concerns the overall ranking of the alternatives based on the attribute-wise ranking as well as the interaction and the combination of the attributes. The compensation model of multi-attribute decision making is applied to N-version software selection. N-version programming is one of the well-known software development approach which ensures high dependability and fault tolerance of software. However, the problem of extra resource involvement arises since the N-version programming stipulates program redundancy. A set of characteristics/attributes have to be considered when choosing an optimal variant of N-version software. The proposed compensation model of multi-attribute decision making provides a solution to this problem. Additionally, a case study on choosing N-version software for a real-life information and control system problem is provided to verify the correctness of our model.