mlsanityData to 13 Oct 2026

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

arXiv 2601.02504 ↗First posted 5 Jan 2026cs.SE cs.AI cs.CYcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 13 of its 35 references that are in the map. First posted on arXiv 5 Jan 2026.

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References · 13

  1. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,196
  2. 2023A Survey on Evaluation of Large Language Modelscited by 1,236
  3. 2024LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigationcited by 93
  4. 2024CodeAid: Evaluating a Classroom Deployment of an LLM-based Programming Assistant that Balances Student and Educator Needscited by 82
  5. 2023CodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classescited by 72
  6. 2023How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debuggingcited by 30
  7. 2024Evaluating Language Models for Generating and Judging Programming Feedbackcited by 8
  8. 2025Static Analysis as a Feedback Loop: Enhancing LLM-Generated Code Beyond Correctnesscited by 7
  9. 2025Combining Large Language Models with Static Analyzers for Code Review Generationcited by 6
  10. 2024BugSpotter: Automated Generation of Code Debugging Exercisescited by 5
  11. 2024Bridging Education and Development: IDEs as Interactive Learning Platformscited by 3
  12. 2024One Step at a Time: Combining LLMs and Static Analysis to Generate Next-Step Hints for Programming Taskscited by 3
1 more
  1. 2021Mapping breakpoint types: an exploratory studycited by 1

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  1. 2025DebugTA: An LLM-Based Agent for Simplifying Debugging and Teaching in Programming Education
  2. 2026DebugHarness: Emulating Human Dynamic Debugging for Autonomous Program Repair
  3. 2025From Code Generation to Software Testing: AI Copilot with Context-Based RAG
  4. 2026Empowering Autonomous Debugging Agents with Efficient Dynamic Analysis
  5. 2025Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency
  6. 2025debug-gym: A Text-Based Environment for Interactive Debugging
  7. 2026TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code
  8. 2025Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models