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Author: search.filters.author.Dayananda I.H.M.B.L

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    CodeHarbor: A Code Analysis Tool
    (Springer Science and Business Media Deutschland GmbH, 2026) Dewmin T.Y; Kodithuwakku Y.S.; Dayananda I.H.M.B.L; Fernando K.R.A.W; De Silva D.I; Rathnayake S.
    As software systems grow more complex, developers face increasing challenges in maintaining and evolving codebases, often resulting in higher costs and longer development cycles. To address these issues, this study presents CodeHarbor, an intelligent tool that integrates machine learning with code analysis to simplify complex code segments. CodeHarbor calculates complexity metrics and offers personalized, context-aware suggestions for improving code quality. By automating code reviews, detecting anomalies, and recommending optimized refactoring strategies, it enables early issue resolution and enhances maintainability. The backend leverages artificial intelligence to identify patterns, enforce coding standards, and generate actionable insights, while the intuitive frontend provides real-time feedback, visualizations, and detailed improvement summaries. CodeHarbor also highlights repetitive patterns and compliance issues, helping developers track progress and reduce manual review effort. With its seamless integration of analysis and interface, CodeHarbor streamlines development workflows and promotes sustainable, high-quality software engineering.