Intelligent Defect Triage Automation (IDTA): Leveraging AI for Efficient Defect Management
Jagan Mohan Rao Doddapaneni · International Journal For Multidisciplinary Research · 2025
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.