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Identifying code quality issues can be tackled; however, implementing code quality improvements can be a complex and time\u2010consuming task. To address this problem, we present a novel methodology designed to assist developers by suggesting alternative code snippets that not only match the functionality of the original code but also improve its quality based on predefined metrics. Our system is based on a language\u2010agnostic approach that allows the analysis of code snippets written in different programming languages. It employs advanced techniques to assess functional similarity and evaluates syntactic similarity, suggesting alternatives that minimize the need for extensive modification. The evaluation of our system on multiple axes demonstrates the effectiveness of our approach in providing usable code alternatives that are both functionally equivalent and syntactically similar to the original snippets, while significantly improving quality metrics. 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