International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | ChatDBG+: Augmenting Debugging with Large Language Models |
|---|---|
| ABSTRACT | Debugging modern software across heterogeneous toolchains remains time-consuming and error-prone. We present AI Debug Console, a unified command-line tool that runs single files and full projects, captures outputs and diagnostics, and---upon failure---enters an interactive debugging loop augmented by delta minimization and optional error localization. The system supports multiple language toolchains (Python, Java, JavaScript/TypeScript, C/C++) and can operate with a model via google-generativeai for enriched assistance. We describe the architecture, implementation, delta approach, and demonstrate behavior across compile-time and runtime failure scenarios. |
| AUTHOR | SHANKER SARJI P, MINCHU G M, ROHIT S BANAKAR, SAGAR YALIGAR, RAJESHWARI M Assistant Professor, Department of CS&E, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India U.G. Students, Department of CS&E, Bapuji Institute of Engineering and Technology, Davanagere, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312028 |
| pdf/28_ChatDBG+ Augmenting Debugging with Large Language Models.pdf | |
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