Problem
Research questions and friction points this paper is trying to address.
Technical Debt
Maintenance Prioritization
Software Evolution
Friction
Refactoring
Technical Debt Friction for Maintenance Prioritization: An Industrial Multi-Case Study
🤖 AI Summary
This study addresses the limitations of existing metrics—such as code health, change hotspots, and coupling—in comprehensively capturing the actual burden of software maintenance. To this end, the paper introduces the concept of “technical debt friction” and validates it through a multi-case industrial study. By integrating multidimensional analytical artifacts—including code health indicators, change hotspots, module coupling, refactoring candidates, and socio-technical network data—the authors collaboratively evaluate with practitioners the construct’s explanatory power and practical utility in maintenance prioritization decisions. Findings show that file-level friction strongly aligns with known problematic areas and subsequent maintenance activities, while project-level friction distributions reveal distinct system evolution patterns. These results demonstrate the effectiveness of technical debt friction as an operationalizable measure of maintenance burden and highlight its potential for supporting real-world decision-making.
📝 Abstract
Software-intensive organizations need effective ways to identify where maintenance and refactoring efforts will yield the greatest practical benefit. Although software analytics such as code health, hotspots, and coupling provide valuable signals, they do not always capture the experienced burden of change that slows software evolution in practice. This paper presents a multi-case industrial study of technical debt friction as a prioritization-oriented concept for identifying where technical debt most strongly affects maintenance and evolution. We investigate how practitioners interpret the concept, whether friction-related analysis aligns with perceived maintenance pain points and refactoring needs, and what broader maintenance and evolution insights friction can provide beyond individual refactoring candidates. To this end, we conducted structured walkthrough sessions with practitioners across multiple industrial cases using analysis artifacts including code health, hotspots, coupling, refactoring targets, and socio-technical views. Our findings show that practitioners generally considered technical debt friction useful for reasoning about maintenance burden, especially when interpreted together with complementary technical and socio-technical views. At the file level, friction often aligned with known problematic areas and, in several cases, with files that later received maintenance attention, although its practical relevance depended strongly on context. In addition, our exploratory project-level analysis suggests that friction distributions may reveal broader maintenance and evolution patterns. These results indicate that technical debt friction is promising as a decision-support concept, but most effective when used with contextual knowledge and supporting evidence.
Innovation
Methods, ideas, or system contributions that make the work stand out.
technical debt friction
maintenance prioritization
socio-technical analysis
multi-case industrial study
software evolution
🔎 Similar Papers
No similar papers found.
💼 Related Jobs
