Quantifying Software Maintainability: A Metric-Based Approach for Code Refactoring and Optimization
Keywords:
Software Maintainability, Code Quality, Refactoring, Maintainability Metrics, Software Development Lifecycle, AI-driven Automation, Technical Debt, Software Complexity, Code Readability, Software EvolutionAbstract
The durability and operational effectiveness together with adaptability of software depends heavily on maintainability elements. Enhancing software complexity produces challenges in code quality management while performance maintenance requires appropriate strategies along with developed tools. The research investigates major aspects of maintainability through an evaluation of measurement tools and code transformation practices and employee-related factors. This work studies contemporary approaches including AI-powered automation and best best practices to implement maintainability during the software development lifecycle sequence. Research analysis supported by industry trends enables this paper to present solutions for routine maintainability problems and established future methods which enhance software sustainability. The study demonstrates why maintainability enhancement requires planned refactoring with suitable metrics and artificial intelligence technology adoption. The analysis explores genuine business implications for software maintainability which affect developers alongside organizations because ongoing process enhancement remains essential. Research approaches for the upcoming years will focus on developing AI reframing mechanisms while improving maintainability evaluation system methods.
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