Published on: April 2026
THE AUTONOMOUS DEBUGGER
G Keerthana B Mallikarjun Reddy G Manirathan N Utkarsh
V. Vanaja
Department of CSE (Data Science) ACE Engineering College Hyderabad Telangana India
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Abstract
The system uses an Agentic AI + RAG architecture to analyze error logs using Sentence Transformers and retrieve relevant faulty code from a ChromaDB vector database. Llama 3 (via Groq) then reasons over the error context and source code to generate accurate, syntax-valid, and logically consistent patches.
All fixes are validated in a secure sandbox environment before being auto-committed to the repository. This enables fully autonomous recovery of CI/CD pipelines, transforming DevOps into an AI-driven, self-healing system that reduces downtime and accelerates software delivery.
How to Cite this Paper
Keerthana, G., Reddy, B. M., Manirathan, G. & Utkarsh, N. (2026). The Autonomous Debugger. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.199
Keerthana, G, et al.. "The Autonomous Debugger." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.199.
Keerthana, G,B Reddy,G Manirathan, and N Utkarsh. "The Autonomous Debugger." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.199.
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- •Peer Review Type: Double-Blind Peer Review
- •Published on: Apr 10 2026
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