Cognitive Maps as a Tool of Estimating Software Quality Based on Standard Requirements

The article shows the use of cognitive maps to estimate and upgrade software quality according to standard GOST R ISO/MEK 25010 – 2015. Expediency of using cognitive map for visualization and formal analysis of interaction between quality characteristics was substantiated and the role of hierarchy analysis method (MAI) in expert appraisal aggregation was shown. The goal of raising software quality was formulated in order to maintain functional suitability at the rate of 0.9 and detail calculations were provided both in static and dynamic model of cognitive map with regard to controlled factors, such as team skills and architecture complexity. At the same time results of using MAI was discussed to identify weight figures, which could help evaluate each factor in the final level of quality. The analysis was verified by current research in the field of cognitive modeling and quality management.

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Publication Details

Journal
Vestnik of the Plekhanov Russian University of Economics
Published
2025-05-15
DOI
https://doi.org/10.21686/2413-2829-2025-3-61-67
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
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article

Cognitive Maps as a Tool of Estimating Software Quality Based on Standard Requirements

A. A. Drozhkin
Vestnik of the Plekhanov Russian University of Economics
Cognitive Science and Mapping
article

Cognitive Maps as a Tool of Estimating Software Quality Based on Standard Requirements

A. A. Drozhkin
article en

Abstract

The article shows the use of cognitive maps to estimate and upgrade software quality according to standard GOST R ISO/MEK 25010 – 2015. Expediency of using cognitive map for visualization and formal analysis of interaction between quality characteristics was substantiated and the role of hierarchy analysis method (MAI) in expert appraisal aggregation was shown. The goal of raising software quality was formulated in order to maintain functional suitability at the rate of 0.9 and detail calculations were provided both in static and dynamic model of cognitive map with regard to controlled factors, such as team skills and architecture complexity. At the same time results of using MAI was discussed to identify weight figures, which could help evaluate each factor in the final level of quality. The analysis was verified by current research in the field of cognitive modeling and quality management.

Vestnik of the Plekhanov Russian University of Economics(3)
Plekhanov Russian University of Economics (RU)
Openalex Percentile: Top 95%
Cognitive Science and Mapping
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