AI based Code Error Explainer using Gemini Model
This paper discusses a new AI tool that helps people learn programming by explaining code errors in languages like Python, C, and Java. It aims to make learning programming easier and more accessible.
This video presentation explains the key concepts from the paper in plain language.
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- 1 The tool provides real-time error detection and explanations.
- 2 It supports multiple programming languages.
- 3 User feedback shows it significantly helps learners understand coding concepts.
- 4 Future improvements will include more languages and interactive features.
Introduction
The introduction highlights the challenges in programming education, particularly the lack of adaptable, language-agnostic tools for code explanation and error detection. It emphasizes the need for a comprehensive educational resource that supports learners in multiple programming languages, addressing the fragmentation in programming education.
Iv. Results And Analysis
The results demonstrate the effectiveness of the AI Based Code Error Explainer in providing multi-language support, achieving over 95% accuracy in error detection, and delivering clear, actionable explanations. User feedback indicates significant improvements in understanding coding concepts and rectifying errors.
Future Scope
Future developments for the project include expanding language support, refining AI models for better accuracy, integrating interactive learning modules, and collaborating with educational platforms to enhance usability and effectiveness.
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Figures Explained
The paper’s visual material highlights the workflow and the main system components.
- Fig 5: Error explanation of C code. Illustrates the system’s capability to provide detailed explanations for errors in C programming.
- Fig 7: Error explanation of Go code. Demonstrates the tool’s functionality in explaining errors across different programming languages.
Conclusion
The conclusion underscores the transformative potential of the AI Based Code Error Explainer in enhancing programming education, emphasizing its role in democratizing access to quality resources and the importance of adaptive tools in the educational landscape.
Frequently Asked Questions
This paper discusses a new AI tool that helps people learn programming by explaining code errors in languages like Python, C, and Java. It aims to make learning programming easier and more accessible.
The introduction highlights the challenges in programming education, particularly the lack of adaptable, language-agnostic tools for code explanation and error detection. It emphasizes the need for a comprehensive educational resource that supports.
The results demonstrate the effectiveness of the AI Based Code Error Explainer in providing multi-language support, achieving over 95% accuracy in error detection, and delivering clear, actionable explanations. User feedback indicates significant.
Yes. PDFDigest can turn this paper into a structured explanation, key takeaways, visual summaries, and a narrated video when available.