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

TL;DR

This paper presents an AI-powered debugging assistant integrated into IDEs that offers real-time support, improving debugging efficiency and effectiveness through advanced analysis and user-centered evaluation.

Contribution

It introduces a novel real-time debugging tool using RAG, LLMs, and heuristics, with comprehensive evaluation in technical, UX, and educational contexts.

Findings

Enhanced debugging efficiency in technical tests

Positive user experience feedback from UX study

Improved debugging skills in classroom tests

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.