AUTOMATED SOFTWARE DEBUGGING AND OPTIMIZATION IN CLOUD-BASED ENVIRONMENTS USING AI-DRIVEN CODE ANALYSIS

Abstract

The present invention provides an AI-driven system and method for automated software debugging and optimization in cloud-based environments. The system integrates a multi-layered architecture comprising an AI debugging engine, a cloud environment monitoring module, an optimization manager, and a feedback mechanism. The AI debugging engine employs static and dynamic code analysis to identify software bugs and performance inefficiencies, while the monitoring module tracks real-time application metrics such as latency, throughput, and resource utilization. The optimization manager suggests or autonomously applies enhancements, including resource allocation, code refactoring, and runtime adjustments. A feedback module enables continuous learning by refining the AI models based on resolved issues, ensuring adaptability to evolving cloud technologies such as microservices, serverless computing, and multi-cloud systems. This invention significantly reduces debugging time, enhances software reliability, and optimizes

Specification

Description:The embodiments of the present invention generally relates to automated software debugging and optimization systems, specifically those designed for use in cloud-based environments. It employs artificial intelligence (AI) and machine learning (ML) to detect, diagnose, and rectify software issues while optimizing performance in real-time. This invention addresses the challenges of maintaining software reliability and efficiency in distributed cloud computing systems.
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.

In recent years, the adoption of cloud computing has transformed how organizations deploy a , Claims:1. A system for automated software debugging and optimization in cloud-based environments, comprising:
an AI debugging engine configured to analyze source code and execution logs for identifying errors;
a cloud environment monitoring module to track performance metrics in real time;
an optimization manager for suggesting or implementing performance enhancements; and
a feedback module for iteratively improving the debugging model based on resolved issues.

2. A method for automated software debugging in cloud environments, comprising the steps of:
receiving software code as input;
performing AI-driven static and dynamic analysis to identify errors;
generating correction recommendations or autonomously applying fixes;
monitoring cloud-based application performance; and
updating the AI model based on debugging outcomes.

3. The system of claim 1, wherein the AI debugging engine employs natural language processing for understanding code comments and documentation to enhance bug detection accuracy.

4. The method

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