Version 1
: Received: 26 October 2024 / Approved: 27 October 2024 / Online: 28 October 2024 (13:23:31 CET)
How to cite:
Patil, A.; Jadon, A. Next-Generation Bug Reporting: Enhancing Development with AI Automation. Preprints2024, 2024102106. https://doi.org/10.20944/preprints202410.2106.v1
Patil, A.; Jadon, A. Next-Generation Bug Reporting: Enhancing Development with AI Automation. Preprints 2024, 2024102106. https://doi.org/10.20944/preprints202410.2106.v1
Patil, A.; Jadon, A. Next-Generation Bug Reporting: Enhancing Development with AI Automation. Preprints2024, 2024102106. https://doi.org/10.20944/preprints202410.2106.v1
APA Style
Patil, A., & Jadon, A. (2024). Next-Generation Bug Reporting: Enhancing Development with AI Automation. Preprints. https://doi.org/10.20944/preprints202410.2106.v1
Chicago/Turabian Style
Patil, A. and Aryan Jadon. 2024 "Next-Generation Bug Reporting: Enhancing Development with AI Automation" Preprints. https://doi.org/10.20944/preprints202410.2106.v1
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.
Keywords
Automated Bug Reporting; Bug Creation; Data Collection; Duplicate Detection; Failure Detection; Large Language Models; Machine Learning; Report Formatting; Severity Assessment; Quality Metrics
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
