Architectural Degradation: Definition, Motivations, Measurement and Remediation Approaches
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912492712624128 |
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| author | Ahmad, Noman Su, Ruoyu Esposito, Matteo Janes, Andrea Lenarduzzi, Valentina Taibi, Davide |
| author_facet | Ahmad, Noman Su, Ruoyu Esposito, Matteo Janes, Andrea Lenarduzzi, Valentina Taibi, Davide |
| contents | Architectural degradation, also known as erosion, decay, or aging, impacts system quality, maintainability, and adaptability. Although widely acknowledged, current literature shows fragmented definitions, metrics, and remediation strategies. Our study aims to unify understanding of architectural degradation by identifying its definitions, causes, metrics, tools, and remediation approaches across academic and gray literature. We conducted a multivocal literature review of 108 studies extracting definitions, causes, metrics, measurement approaches, tools, and remediation strategies. We developed a taxonomy encompassing architectural, code, and process debt to explore definition evolution, methodological trends, and research gaps. Architectural degradation has shifted from a low-level issue to a socio-technical concern. Definitions now address code violations, design drift, and structural decay. Causes fall under architectural (e.g., poor documentation), code (e.g., hasty fixes), and process debt (e.g., knowledge loss). We identified 54 metrics and 31 measurement techniques, focused on smells, cohesion/coupling, and evolution. Yet, most tools detect issues but rarely support ongoing or preventive remediation. Degradation is both technical and organizational. While detection is well-studied, continuous remediation remains lacking. Our study reveals missed integration between metrics, tools, and repair logic, urging holistic, proactive strategies for sustainable architecture. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_14547 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Architectural Degradation: Definition, Motivations, Measurement and Remediation Approaches Ahmad, Noman Su, Ruoyu Esposito, Matteo Janes, Andrea Lenarduzzi, Valentina Taibi, Davide Software Engineering Architectural degradation, also known as erosion, decay, or aging, impacts system quality, maintainability, and adaptability. Although widely acknowledged, current literature shows fragmented definitions, metrics, and remediation strategies. Our study aims to unify understanding of architectural degradation by identifying its definitions, causes, metrics, tools, and remediation approaches across academic and gray literature. We conducted a multivocal literature review of 108 studies extracting definitions, causes, metrics, measurement approaches, tools, and remediation strategies. We developed a taxonomy encompassing architectural, code, and process debt to explore definition evolution, methodological trends, and research gaps. Architectural degradation has shifted from a low-level issue to a socio-technical concern. Definitions now address code violations, design drift, and structural decay. Causes fall under architectural (e.g., poor documentation), code (e.g., hasty fixes), and process debt (e.g., knowledge loss). We identified 54 metrics and 31 measurement techniques, focused on smells, cohesion/coupling, and evolution. Yet, most tools detect issues but rarely support ongoing or preventive remediation. Degradation is both technical and organizational. While detection is well-studied, continuous remediation remains lacking. Our study reveals missed integration between metrics, tools, and repair logic, urging holistic, proactive strategies for sustainable architecture. |
| title | Architectural Degradation: Definition, Motivations, Measurement and Remediation Approaches |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2507.14547 |