AI-ASSISTED SOFTWARE CODE REFACTORING TOOL

Abstract

The present invention relates to an AI-assisted software code refactoring tool that automates the identification of inefficiencies, code smells, and design flaws in software code. By utilizing advanced artificial intelligence techniques, such as natural language processing and machine learning, the tool analyzes code to suggest optimized refactorings that improve code quality, readability, maintainability, and performance without altering its functionality. The tool integrates seamlessly with development environments and CI/CD pipelines, offering real-time, context-aware suggestions and continuously learning from user feedback to enhance its recommendations. This invention aims to streamline the refactoring process, reduce technical debt, and accelerate software development.

Specification

Description:The present invention relates to the field of software development, specifically to automated code refactoring tools. It leverages artificial intelligence (AI) and machine learning (ML) techniques to enhance software code quality by identifying inefficiencies, reducing complexity, and suggesting optimized refactoring options. The invention is designed to assist developers in improving code readability, maintainability, and performance without altering the original functionality of the software.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.

Software development is a dynamic and complex process that inv , Claims:1. A system for AI-assisted software code refactoring, comprising:
• A code analysis engine configured to analyze source code and identify code inefficiencies and anti-patterns using static and dynamic code analysis techniques;
• An AI-based refactoring module that utilizes machine learning models to generate refactoring suggestions based on the identified inefficiencies;
• A feedback loop mechanism for receiving user inputs on the generated suggestions, wherein the AI-based refactoring module adapts its future suggestions based on this feedback;
• A compatibility assessment module that evaluates the impact of the refactoring on software performance and system integration;
• An interface module to display the refactoring suggestions and facilitate user interaction.

2. The system of claim 1, wherein the AI-based refactoring module uses a combination of natural language processing and reinforcement learning techniques to analyze the semantic and syntactic structure of the code and suggest optimizations.

3. Th

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