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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM42592

AIRA : AI-Powered Code Review & Bug Detection System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM42592

Volume:

9 |

3 |

Mar 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM42592

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MK

Manish Kumar1

MKS

Manish Kumar Shah2

AB&PAK

Aparajita Biswal & Prof. Amit Kumar

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Abstract

The increasing complexity of software develop- ment presents significant challenges for developers, including bug detection, code inefficiencies, and security vulnerabilities. Traditional methods of code review and debugging often result in increased workload and reduced productivity. To address these issues, AI-powered tools are emerging as a solution to enhance code quality, streamline development, and minimize human error. Introducing AIRA (AI-powered Intelligent Review Assistant), an advanced AI-driven code review and bug detection system designed to assist developers in improving code quality and ensuring robust security. AIRA leverages advanced AI models, including Pylint, SonarQube, and Bandit, to perform real- time static and dynamic code analysis. It identifies bugs, security vulnerabilities, and performance bottlenecks, providing actionable insights to enhance code efficiency. AIRA is built on a Flask-based Python backend integrated with a React.js frontend, offering a high-performance and intuitive interface. The system supports real-time code analysis, automated code optimization, and AI-based refactoring, en- abling developers to identify and resolve issues efficiently. AIRA also features a secure authentication system using Firebase, providing multi-platform support and seamless user experience with light and dark mode options. AIRA empowers developers by automating repetitive tasks, reducing the time required for code review, and enhancing overall code quality. By combining AI-driven analysis with an intuitive user interface, AIRA aims to transform the software development process, making it faster, more secure, and highly efficient.

KEYWORDS

AI-powered Code Review Bug Detection Python Development Flask API Security Analysis Static Code Anal- ysis AI-Based Code Optimization Code Efficiency Software Security AIRA.

Cite This Article

Manish Kumar1, Manish Kumar Shah2, Aparajita Biswal & Prof. Amit Kumar, "AIRA : AI-Powered Code Review & Bug Detection System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 3, Mar 2025. https://doi.org/10.55041/IJSREM42592

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Publication Date

3/18/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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