WIP: Chat-Debugging: Large Language Model as a Hardware Debugging Assistant
2026-08-03 • Human-Computer Interaction
Human-Computer InteractionComputers and Society
AI summaryⓘ
The authors studied how a large language model (LLM) can help electrical engineering students debug physical hardware circuits, which can be frustrating and hard to learn. They focused on a method called Chat-Debugging, where the LLM assists students by understanding hardware details and natural language. Their research with a senior student showed that this approach boosts confidence and helps students solve problems by exploring multiple possible causes and actively guiding the LLM. The interaction works best when the student takes charge and corrects any mistakes the LLM makes.
hardware debugginglarge language modelselectrical engineering educationanalog circuitsdigital circuitsmixed-signal circuitshuman-computer interactionconstant comparative analysisdebugging confidencenatural language processing
Authors
Andrew Ash, John Hu
Abstract
This work-in-progress research paper explores Chat-Debugging, a novel use case for large language models as an assistant for hardware debugging tasks to improve students' debugging skills. Hardware debugging can be a time-consuming and stressful skill to develop, leading to frustration and other negative emotions. While past work has explored streamlining and automating software-based circuit debugging where digital circuits are dominant, Chat-Debugging aids in physical hardware debugging where circuits may be analog, digital, or mixed-signal. Qualitative data were collected from LLM chat logs and interviews with a fourth-year electrical engineering undergraduate student. Major themes were extracted using a constant comparative analysis. Chat-Debugging incorporates accurate hardware information, properly handles natural language descriptions of circuits, and improves debugging confidence. A successful Chat-Debugging session includes investigating multiple potential root causes proposed by the LLM, the patience and determination to eliminate root causes, and a student who leads the debugging process by assertively correcting the LLM's misunderstandings. This human-computer interaction can improve electrical and computer engineering students' confidence during debugging and improve their debugging skills.