Enhancing Debugging Skills with AI-Powered Assistance: A Real-Time Tool for Debugging Support

• URL: http://arxiv.org/abs/2601.02504v1
• Date: Mon, 05 Jan 2026 19:20:59 GMT
• Title: Enhancing Debugging Skills with AI-Powered Assistance: A Real-Time Tool for Debugging Support
• Authors: Elizaveta Artser, Daniil Karol, Anna Potriasaeva, Aleksei Rostovskii, Katsiaryna Dzialets, Ekaterina Koshchenko, Xiaotian Su, April Yi Wang, Anastasiia Birillo,
• Abstract summary: It offers real-time support by analyzing code, suggesting breakpoints, and providing contextual hints.<n>Using RAG with LLMs, program slicing, and customs, it enhances efficiency by minimizing LLM calls and improving accuracy.
• Score: 8.607022377771422
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Debugging is a crucial skill in programming education and software development, yet it is often overlooked in CS curricula. To address this, we introduce an AI-powered debugging assistant integrated into an IDE. It offers real-time support by analyzing code, suggesting breakpoints, and providing contextual hints. Using RAG with LLMs, program slicing, and custom heuristics, it enhances efficiency by minimizing LLM calls and improving accuracy. A three-level evaluation - technical analysis, UX study, and classroom tests - highlights its potential for teaching debugging.

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