AI-Powered SQL Bug Analyzer and Auto Fix Assistant

Article Sidebar

Main Article Content

Dr. V. S. Gaikwad
Ganesh Borole
Omkar Jadhav
Himanshu Tambe
Krishna Kinikar

This work describes the development of a system based on AI and chat technology that allows users to communicate with several databases by posing questions in natural language. Standard databases require knowledge of SQL and technical skills from their users; therefore, they are difficult to use for individuals who lack expertise in computer science and programming. In this work, we incorporate MERN stack technology and integrate AI technology within it to translate user commands into valid queries for databases. Our proposed system is capable of processing queries and communicating with different types of databases, including MongoDB, MySQL, SQLite, and BigQuery..

AI-Powered SQL Bug Analyzer and Auto Fix Assistant. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(5), 3090-3099. https://doi.org/10.51583/IJLTEMAS.2026.150500252

Downloads

References

Z. Zhong, C. Xiong, and D. Yu, ”Seq2SQL: Generat ing Structured Queries from Natural Language Using Reinforcement Learning,” in Proc. ACM SIGMOD, pp. 1913–1927, 2017.

Yu, Z. Zhang, and D. Yu, ”Spider: A Large Scale Human- Labeled Dataset for Complex and Cross Domain Semantic Parsing and Text-to-SQL Task,” in Proc. EMNLP, pp. 3911–3921, 2018

Wang, X. Liu, and M. Richardson, ”RAT-SQL: Relation-Aware Schema Encoding and Linking for Text to- SQL Parsers,” in Proc. ACL, pp. 7567–7578, 2020. OpenAI, ”GPT-4 Technical Report,” arXiv preprint arXiv:2303.08774, 2023.

Z. Hong, J. Xu, and Y. Chen, ”MetaGPT: Meta Pro gramming for Multi-Agent Collaboration,” arXiv preprint arXiv:2308.00352, 2023.

S. Sergeyuk, L. Mironova, and A. Pashkov, ”Using AI Based Coding Assistants in Practice: A Large-Scale Sur vey,” Journal of Software Engineering Research, vol. 12, no. 3,

pp. 215–228, 2024.

J. Lee, K. Park, and S. Choi, ”FixAgent: A Multi-Agent Framework for Automated Debugging and Code Repair,” in Proc. IEEE Int. Conf. on Artificial Intelligence and Data Science (AIDAS), pp. 88–95, 2024.

L. Wang, Y. Qian, and D. Zhou, ”MAC-SQL: Multi-Agent Collaboration for Robust Text-to-SQL Parsing,” in Proc. AAAI Conf. on Artificial Intelligence, pp. 12765–12773, 2024.

H. Gao, Y. Sun, and X. Li, ”Enhancing Semantic Con sistency in Text-to-SQL Generation with Context-Aware Reasoning,” in Proc. NAACL, pp. 6432–6445, 2024.

H. Gao, Y. Sun, and X. Li, ”Enhancing Semantic Con sistency in Text-to-SQL Generation with Context-Aware Reasoning,” in Proc. NAACL, pp. 6432–6445, 2024.

Y. Cen, K. Liu, and H. Li, ”SQLFixAgent: Towards Semantic- Accurate Text-to-SQL Parsing via Consistency Enhanced Multi-Agent Framework,” arXiv preprint arXiv:2503.01234, 2025.

OpenAI, “Codex: Evaluating Large Language Models for Code Generation,” OpenAI Research Publication, 2021.

J. Austin, A. Odena, M. Nye, et al., “Program Synthesis with Large Language Models,” arXiv preprint arXiv:2108.07732, 2021.

Y. Sun, T. Gao, and H. Li, “Improving Semantic Accuracy in Text-to-SQL Systems Using Reflective Query Validation,” in Proc. International Conference on Computational Linguistics (COLING), pp. 4521–4533, 2023.

AutoGPT Team, “AutoGPT: An Autonomous GPT-4 Experiment for Complex Task Solving,” GitHub Repository, 2023. [Online]. Available: https://github.com/Significant-Gravitas/AutoGPT

JetBrains, “JetBrains AI Assistant: Intelligent Coding Support for Developers,” JetBrains Official Documentation, 2024. [Online]. Available: https://www.jetbrains.com/ai/

Tabnine, “Tabnine AI Code Assistant for Software Development,” Tabnine Official Documentation, 2024. [Online]. Available: https://www.tabnine.com/

Microsoft, “Azure OpenAI Service for Intelligent Database Query Assistance,” Microsoft Documentation, 2024. [Online].Available: https://learn.microsoft.com/

Google Cloud, “AI-Powered Database Query Optimization Using Generative AI,” Google Cloud Research, 2024.

Article Details

How to Cite

AI-Powered SQL Bug Analyzer and Auto Fix Assistant. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(5), 3090-3099. https://doi.org/10.51583/IJLTEMAS.2026.150500252