Architectural Degradation: Definition, Motivations, Measurement and Remediation Approaches

2025-07-19

AI Summary

This study addresses the ambiguous definition, fragmented measurement, and disjointed remediation of software architecture degradation. Through a multilingual systematic literature review encompassing 108 studies, it establishes the first unified taxonomy integrating both technical and socio-technical dimensions. Methodologically, it synthesizes academic and industrial perspectives to propose a tripartite debt classification framework—“architecture–code–process”—and synthesizes 54 measurement metrics and 31 assessment techniques, focusing on architectural bad smells, modularization flaws, and evolutionary anomalies. Key contributions include: (1) revealing the inherent evolution of architecture degradation from a purely technical concern to a socio-technical phenomenon; (2) identifying the prevailing tool limitation of overemphasizing detection while underprioritizing repair; and (3) proposing a continuous governance framework supported by automated repair integration and cross-organizational collaboration, thereby advancing sustainable software architecture practices.

Technology Category

• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Agent/AI Theories and Architectures
• Machine Learning: Deep Neural Architectures and Foundation Models

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Models for Web evolution
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

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.

Problem

• Unifying fragmented definitions and metrics of architectural degradation
• Identifying causes and remediation strategies for system quality erosion
• Addressing gaps in continuous architectural degradation detection and repair

Innovation

• Unified taxonomy for architectural degradation analysis
• Multivocal literature review of 108 studies
• Identified 54 metrics and 31 measurement techniques