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Looking for experience!

DevBug-AI is an AI-powered system that automates bug classification and developer recommendation for software teams. As applications scale, bug triage becomes slow and error-prone due to unclear reports, inconsistent categorization, and manual assignment. DevBug-AI removes this bottleneck by intelligently analyzing bug reports and assigning them to the most suitable developers. Using natural language processing and machine learning, the system classifies bugs from their title and description and recommends the top three developers based on historical bug data, domain, and tech stack. Confidence scores are provided to support reliable decision-making. The solution is built as a Streamlit web app with a unified ML pipeline. It uses TF-IDF and sentence embeddings for text understanding, Scikit-learn for bug classification, and LightGBM for developer recommendation. The system is trained on 50,000+ real bug reports and gracefully handles unseen technologies by mapping them to an “Other” category. DevBug-AI reduces triage time, improves assignment accuracy, and enables data-driven bug management at scale. Future work includes integrations with Jira and GitHub, workload-aware recommendations, and LLM-based bug summarization—making it a practical, production-oriented AI solution for modern engineering teams.
7 Feb 2026