This research demonstrates how machine learning techniques can effectively distinguish between actual bug reports and misclassified requests, potentially saving significant developer time and resources.

• Over 30% of bug reports in large software projects are misclassified, causing wasted engineering effort
• Machine learning models can automatically categorize issue reports with high accuracy
• Proper classification improves prioritization, resource allocation, and system reliability
• Results provide practical guidance for implementing ML-based bug triage systems

For engineering teams, this approach offers a scalable solution to the persistent challenge of bug report management, reducing manual inspection time and accelerating the development cycle.

An Empirical Study on the Classification of Bug Reports with Machine Learning