Intelligent Defect Triage Automation (IDTA): Leveraging AI for Efficient Defect Management

Author(s)	Jagan Mohan Rao Doddapaneni
Country	United States
Abstract	With the increasing complexity of software development, defect management has become a crucial aspect of ensuring high-quality releases. Traditional defect triage methods involve manual analysis, which is time-consuming and prone to human error. This paper introduces Intelligent Defect Triage Automation (IDTA), an AI-driven approach leveraging historical defect knowledge to streamline the triage process. By integrating a Defect Knowledge Management (DKM) repository and an automated triage engine, IDTA can intelligently assess new defects, match them against historical data, and suggest resolution steps. This automation reduces the time taken for defect analysis, enhances decision-making accuracy, and improves overall software quality.
Keywords	Defect Triage, Root Cause Analysis (RCA), Intelligent Automation, Defect Knowledge Management, AI in Software Testing, Jira Integration
Field	Engineering
Published In	Volume 7, Issue 1, January-February 2025
Published On	2025-02-08
Cite This	Intelligent Defect Triage Automation (IDTA): Leveraging AI for Efficient Defect Management - Jagan Mohan Rao Doddapaneni - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.36893
DOI	https://doi.org/10.36948/ijfmr.2025.v07i01.36893
Short DOI	https://doi.org/g84d86

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International Journal For Multidisciplinary Research