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New and intermediate coders produce code that works but is poorly organized, hard to read, and buggy. Current solutions (e.g., IDE linters, static checkers, or autoformatters) fix syntax and style but don't instruct why changes matter. Students and junior developers continue to replicate poor practices, leading to technical debt and extended development into professional-level coding. CQE+OST is an intelligent coding guide that automatically enhances raw code into readable, high-performance, and easy-to-maintain code and acts as an on-screen teacher. It marks errors, reformats the code nicely, and comments each fix in simple words. It is a code reviewer/mentor combination. Code Quality Enhancer (CQE): Sanitizes and optimizes submitted code. Fixes bugs, name conflicts, and inefficiencies. Imposes best practices on the target language. On-Screen Teacher (OST): Illustrates side-by-side comparison: original to improved. Annotates changes with reasons ("Renamed variable for clarity," "Used iteration instead of recursion to prevent stack overflow," etc.). Recommends further learning materials (docs, tutorials). Audience : Students & Self-learners: Don't only learn what works, but why. Universities & Bootcamps: Supplement instruction with personalized feedback. Junior Developers: Get real-time mentorship without flooding senior engineers. To be noted : Unlike IDE linters (which report issues but don't explain solutions). More effective than AI code generation tools (which offer solutions but not education). It bridges the gap between functional code and professional code allowing millions of students to build sustainable coding habits. It not only writes better code, but it also develops the thinking that goes into building good software. The Code Quality Enhancer + On-Screen Teacher (CQE+OST) needs a web-based application with a frontend (React + Monaco Editor) to paste/upload code and see side-by-side original and improved versions. The backend is based on language-specific linters/parsers (e.g., clang-tidy for C, pylint for Python) combined with an AI-based layer to provide human-like explanations of the improvements. A sandboxed development environment (Docker) provides secure code analysis, while a PostgreSQL database holds submissions, refactored code, and annotations. Automated refactoring, style and efficiency corrections, and annotated feedback suitable for beginners are core functionalities.
