An AI-Driven Approach to Automatic Code Analysis and Summarization
for Enhanced Software Understanding
Aditya K V S1, Kishore Gowda A1, Sanjay K S1, Prof. Akshatha Preeth P2
1Third Year Student, Department of Information Science and Engineering, Global Academy of Technology
2Assistant Professor, Department of Information Science and Engineering, Global Academy of Technology
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Abstract - The AI-Driven Code Analyzer is an innovative tool designed to address the challenges developers, students, and educators face in understanding complex code. With programming becoming an integral part of various industries, the need for accessible tools that simplify code comprehension has never been greater. This tool allows users to input code and receive detailed, step-by-step explanations of its functionality, helping to demystify programming logic and enhance understanding. Whether it’s a beginner struggling with foundational concepts or an experienced programmer dealing with an unfamiliar codebase, the AI-Driven Code Analyzer serves as a valuable resource for improving productivity and learning efficiency.
At the heart of this tool lies its integration with the Gemini API, a sophisticated backend system that processes inputted code and generates human-readable explanations. This integration ensures a seamless and efficient user experience, providing accurate and insightful breakdowns of even the most complex algorithms. The modular design of the platform allows it to handle diverse programming languages and concepts, making it a versatile solution for various user needs. Complementing its technical prowess is a user-friendly interface that simplifies interaction, enabling users to focus solely on understanding the code rather than navigating the tool itself.
The applications of the AI-Driven Code Analyzer extend far beyond individual use. In educational settings, it can be leveraged as a teaching aid, helping students grasp difficult programming concepts through real-world examples. In professional environments, it can assist developers in debugging, code reviews, and understanding legacy systems, significantly reducing time spent on manual analysis. By streamlining the process of code explanation, this tool not only fosters a deeper understanding of programming but also addresses the growing demand for accessible and intelligent software solutions in an increasingly tech-driven world.
Key Words: Code Analysis, Code Summarization, Code Comprehension, Human-Readable Explanations, Natural Language Processing (NLP), Programming Logic, Collaborative Development, Productivity Enhancement, Educational Applications, System Architecture, Learning Efficiency
