A Study on Efficient Application of Architectural Patterns by the Taxonomy of Software Requirements


KIPS Transactions on Software and Data Engineering, Vol. 12, No. 7, pp. 285-294, Jul. 2023
https://doi.org/10.3745/KTSDE.2023.12.7.285,   PDF Download:
Keywords: Requirements Taxonomy, Requirements Prioritization, Software Architectural Patterns, Software Architecture Design
Abstract

As software grows continuously in scale and complexity, the role of software architecture has become increasingly important across various industries. Although software architects often rely on their experience and intuition when designing such architecture, there is a variety of methodologies being researched for architecture design. However, these methodologies do not address the specific effects of applying multiple architectural patterns to a system or the sequence in which they should be applied. In this study, we explain the variation in architectural design results depending on the order in which the same set of architectural patterns is applied to a single system. Based on this phenomenon, we identify requirements for applying architectural patterns and propose a method of classifying the patterns to be applied. We also propose a prioritization process for requirements to efficiently apply the classified patterns in a specific order. Finally, we show a case study that prioritizing requirements based on architectural pattern types is beneficial for efficient software architecture design in terms of quality attributes.


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Cite this article
[IEEE Style]
J. Choi and S. Y. Min, "A Study on Efficient Application of Architectural Patterns by the Taxonomy of Software Requirements," KIPS Transactions on Software and Data Engineering, vol. 12, no. 7, pp. 285-294, 2023. DOI: https://doi.org/10.3745/KTSDE.2023.12.7.285.

[ACM Style]
Jong-Woo Choi and Sang Yoon Min. 2023. A Study on Efficient Application of Architectural Patterns by the Taxonomy of Software Requirements. KIPS Transactions on Software and Data Engineering, 12, 7, (2023), 285-294. DOI: https://doi.org/10.3745/KTSDE.2023.12.7.285.