Signal WIP: Chat-Debugging: Large Language Model as a Hardware Debugging Assistant

Summary

Andrew Ash and John Hu published a work-in-progress paper on arXiv (cs.CY) on August 3, 2026, describing Chat-Debugging, a large language model assistant designed to help students debug physical hardware circuits that may be analog, digital, or mixed-signal. Unlike prior work that focused on automating software-based digital circuit debugging, Chat-Debugging targets physical hardware debugging, which the authors describe as a time-consuming and often stressful skill to develop. The researchers collected qualitative data from LLM chat logs and interviews with a single fourth-year electrical engineering undergraduate student, analyzing the material using constant comparative analysis. They found that Chat-Debugging incorporates accurate hardware information, handles natural-language circuit descriptions appropriately, and improves the student's debugging confidence. The authors identify conditions for a successful session, including investigating multiple potential root causes proposed by the LLM, patience in eliminating causes, and the student actively correcting the LLM's misunderstandings.