Abstract
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.
The original version of the book was revised. For detailed information please see Erratum. The erratum to the book is available at 10.1007/978-3-319-57141-6_53
An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-57141-6_53
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Gruzenkin, D.V., Grishina, G.V., Durmuş, M.S., Üstoǧlu, I., Tsarev, R.Y. (2017). Compensation Model of Multi-attribute Decision Making and Its Application to N-Version Software Choice. In: Silhavy, R., Silhavy, P., Prokopova, Z., Senkerik, R., Kominkova Oplatkova, Z. (eds) Software Engineering Trends and Techniques in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 575. Springer, Cham. https://doi.org/10.1007/978-3-319-57141-6_16
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DOI: https://doi.org/10.1007/978-3-319-57141-6_16
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