Enhancing Software Development with AI-Driven Code Reviews - Sudheer Peddineni Kalava (North American Journal of Engineering Research, 2024)
The landscape of software development is undergoing a seismic shift with the advent of AI, projected to grow by 37.3% from2023 to 2030, changing how development teams design, develop, document, deliver, and debug software [1]. Amidst thistransformation, AI code review emerges as a pivotal tool, replacing time-consuming manual code reviews prone to causingdeveloper burnout and inefficiency, with data-driven, unbiased analyses capable of scanning vast codebases in seconds [1] [2] .These AI-powered tools not only enhance the overall quality by identifying potential bugs, security vulnerabilities, code smells,and bottlenecks but also maintain accuracy and reduce biases, being entirely data-based [2] .Incorporating AI code review, including ai code review open source, ai based code review tools, ai code review vscode, deepcodeai code review, generative ai code review, free ai code review, best ai code review tools, ai code review gitlab, and approaches tosolving coding issues, holds the promise of revolutionizing code quality [2] [3] [4]. AI algorithms outperform human capabilities byreviewing thousands of lines per second, growing more precise over time, and ensuring consistent coding standards [4] . Thisarticle will explore the key benefits, challenges, top tools, and integration strategies of AI-driven code review in enhancingsoftware development workflows, marking a transformative, not incremental, shift in the development paradigm [4] [5] .