• V Anusha
• N Sri Satya Siva Sai Krishna
• K Sai Priya
• T Venkat Charan
• CH Malleshwar Rao

In the realm of software development, the efficient management of bugs is paramount for product quality and timely delivery. Traditional manual bug triage processes often struggle to cope with the increasing volume and complexity of bugs reported. To address these challenges, automated bug triage systems have emerged as a promising solution. This abstract delves into the significance and functionality of automated bug triage systems. Leveraging machine learning algorithms, natural language processing techniques, and historical bug data analysis, these systems automate the classification and prioritization of incoming bugs based on various factors such as severity, impact, and complexity. By doing so, they streamline bug triage processes, enabling development teams to allocate resources more effectively and resolve critical issues promptly. Key components of an automated bug triage system include data pre-processing, feature extraction, classification models, and iterative learning mechanisms for continuous improvement. Through the utilization of large bug datasets and adaptive algorithms, these systems can evolve and enhance their accuracy over time. The benefits of automated bug triage systems are multi-fold. They alleviate the manual burden associated with bug triage, minimize response times, and bolster overall software quality by ensuring that critical bugs are addressed promptly. Furthermore, by automating repetitive tasks, development teams can devote their efforts to more strategic activities, such as feature enhancement and innovation. However, challenges such as data quality assurance, interpretability of model decisions, and mitigation of algorithmic biases must be diligently addressed to ensure the reliability and fairness of automated bug triage systems. Human intervention remains crucial to validate system outputs and intervene as needed, particularly in cases where automated decisions may have significant ramifications. In conclusion, automated bug triage systems represent a pivotal advancement in software development practices. By harnessing the power of machine learning and data analytic, these systems empower development teams to streamline bug management workflows and deliver high-quality software products efficiently and effectively.

Automated bug triage;Bug classification;Ticket assignment; Artificial Intelligence (AI); Machine Learning;Issue tracing; Natural Language Processing (NLP);Work flows.

"AUTOMTED SOFTWARE BUG TRIAGE SYSYTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.d205-d211, July-2024, Available :http://www.jetir.org/papers/JETIR2407322.pdf

"AUTOMTED SOFTWARE BUG TRIAGE SYSYTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppd205-d211, July-2024, Available at : http://www.jetir.org/papers/JETIR2407322.pdf