Author(s)

Bhavesh Nikam

  • Manuscript ID: 120426
  • Volume 2, Issue 5, May 2026
  • Pages: 155–163

Subject Area: Computer Science

DOI: https://doi.org/10.5281/zenodo.20008212
Abstract

Problem Statement:
As software development accelerates in complexity, manual code reviews and debugging become time- consuming, inconsistent, and error-prone. Developers often lack real-time feedback while coding, leading to quality issues that are discovered late in the development cycle. There is a growing need for intelligent tools that assist developers in reviewing, optimizing, and securing their code — directly within their coding environment.

Proposed Solution:
This project proposes the development of an AI-powered code reviewer that can analyze source code, detect bugs, suggest optimizations, and provide human-readable explanations. The system integrates directly into popular IDEs such as VS Code, Jupyter Notebook, and Sublime Text, enabling real-time, inline feedback for developers. The core engine uses open-source models like CodeT5 and static analysis tools (e.g., Pylint) to deliver suggestions without relying on paid APIs. This intelligent assistant will also simulate pull request feedback generation to mirror industry-grade development workflows.

Keywords
AI-Based Code ReviewStatic Code AnalysisCodeT5CodeBERTAutomated Pull Request ReviewIDE IntegrationSoftware Quality AssuranceNatural Language ExplanationsDeveloper Productivity Enhancement.