Technical Debt Identification in Long-Term Software Projects

Abstract

Technical debt identification is important in long-term software projects because repeated maintenance, urgent fixes, changing requirements, and short-term design compromises can gradually reduce software quality. Long-running projects often accumulate problems such as duplicated code, outdated dependencies, weak documentation, complex modules, poor test coverage, architecture erosion, and unresolved defects. Traditional project monitoring may focus mainly on feature delivery and defect closure, but it may not clearly expose hidden structural weaknesses that increase future maintenance effort. This article focuses on technical debt identification in long-term software projects by examining code smells, complexity metrics, dependency issues, test gaps, documentation weakness, defect recurrence, and refactoring backlog. The study discusses how systematic debt detection can help teams classify debt sources, estimate maintenance risk, prioritize corrective actions, and prevent further design degradation. The article concludes that effective technical debt identification can improve maintainability, reduce long-term project cost, support better refactoring decisions, and strengthen sustainable software evolution.