Next-Generation Bug Reporting: Enhancing Development with AI Automation

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Abstract

In today’s Agile and DevOps-driven software development landscape, the need for rapid and accurate bug reporting is more critical than ever. This paper presents a next-generation automation tool powered by large language models and machine learning, aimed at innovating the bug reporting process. The tool automates every phase of bug reporting, from failure detection to severity assessment, duplicate detection, and report generation. By addressing the limitations of manual bug reporting such as inconsistency, scalability challenges, and time inefficiencies, the proposed solution enhances the software testing workflow. Initial findings demonstrate significant time savings, reduced manual errors, and improved collaboration between testers and developers. This work establishes a foundation for fully automated bug reporting, poised to accelerate software development cycles while maintaining high-quality standards.

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