A Design Method of SPEM-based Feature Methodology Framework
Chee-Yang Song1 & Eun-Sook Cho2 Show affiliations
- Department of Software, Kyungpook National University, Daegu, Korea
- Department of Software Engineering, Seoil University, Seoul, Korea
Journal of Computer Science, Volume 21, Issue 11, pp. 2663–2684 · doi.org/10.3844/jcssp.2025.2663.2684
Abstract
Existing feature methodologies have been presented primarily at the research level, lacking generalized frameworks suitable for commercial application. Critically, the absence of SPEM (Software & Systems Process Engineering Metamodel) standard compliance limits their standardization and systematization, hindering practical adoption. Furthermore, work-product-based feature methodology frameworks that facilitate methodological structuring are needed to address the evolving complexity of software development processes. This paper presents a design method for an SPEM-based feature methodology framework using metamodel principles. The proposed framework adheres to SPEM's method content and method process classification systems, incorporating the fundamental development process elements of role, task, and work product. Specifically, this study introduces a work-product-centric methodology framework aligned with SPEM elements, optimizing methodological structuring capabilities. Additionally, standardized specifications are provided to define activities within feature methodology phases. The feature methodology metamodel is formally specified using Z notation, with metamodel accuracy verified through Z/Eves toolset validation. Standardized SPEM adoption systematizes and enhances the feature methodology, improving usability and accessibility. By structuring existing methodologies around work products to accommodate diverse application and methodology evolution, the framework enables flexible feature development process construction suitable for varied project requirements and organizational contexts.
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Song, C. & Cho, E. (2025). A Design Method of SPEM-based Feature Methodology Framework . Journal of Computer Science, 21(11), 2663–2684. https://doi.org/10.3844/jcssp.2025.2663.2684
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