CompileX: An Intelligent Online Compiler with AI Error Resolution |
Author(s): |
| Ms. Pooja Patil , Usha Mittal Institute of Technology, SNDT Women’s University, Mumbai, India; Ms. Kimaya Ingale, Usha Mittal Institute of Technology, SNDT Women’s University, Mumbai, India; Ms. Renu Meshram, Usha Mittal Institute of Technology, SNDT Women’s University, Mumbai, India; Prof. Aritri Sen, Usha Mittal Institute of Technology, SNDT Women’s University, Mumbai, India |
Keywords: |
| Artificial Intelligence, Online Compiler, Error Resolution, Large Language Models, Programming Education, Web-Based IDE, Code Translation, Debugging Assistance |
Abstract |
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Online compilers have reduced the installation barriers associated with programming education, but conventional compiler interfaces generally expose technical diagnostics without contextual guidance for novice programmers. This paper presents CompileX, an intelligent online compiler that integrates Artificial Intelligence (AI) for error resolution, contextual code explanation, conversational programming assistance, and cross-language code translation. CompileX implements four primary AI modules: (i) an AI Error Resolution Engine that analyzes compiler and runtime errors to generate simplified explanations and debugging guidance, (ii) an AI Chat Panel that provides context-aware conversational assistance using source-code context, (iii) an AI Code Translator supporting translation across five programming languages, and (iv) an Explain This Code module that provides selection-based explanations of source-code segments. The system uses a React.js frontend with Vite, a Flask backend, GCC, G++, JDK, Python, and Node.js runtimes, and an LLM API for AI-assisted code understanding. Evaluation across 500 compilation scenarios reports an overall error explanation accuracy of 91.1%, a 64.7% reduction in average debugging time compared with a compiler-only baseline, and a mean AI response latency of 2.83 seconds. A user evaluation with 45 participants also reports positive scores for explanation clarity, debugging helpfulness, and overall satisfaction. The results indicate that integrating AI assistance directly into a multi-language compiler environment can support error comprehension and reduce debugging effort while preserving conventional compilation and execution workflows. |
Other Details |
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Paper ID: IJSRDV14I80029 Published in: Volume : 14, Issue : 8 Publication Date: 01/11/2026 Page(s): 71-79 |
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