On Repairing Quantum Programs Using ChatGPT
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Abstract (arXiv)
Automated Program Repair (APR) is a vital area in software engineering aimed at generating automatic patches for vulnerable programs. While numerous techniques have been proposed for repairing classical programs, the realm of quantum programming lacks a comparable automated repair technique. In this initial exploration, we investigate the use of ChatGPT for quantum program repair and evaluate its performance on Bugs4Q, a benchmark suite of quantum program bugs. Our findings demonstrate the feasibility of employing ChatGPT for quantum program repair. Specifically, we assess ChatGPT's ability to address bugs within the Bugs4Q benchmark, revealing its success in repairing 29 out of 38 bugs. This research represents a promising step towards automating the repair process for quantum programs.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jan 2024.
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Citing papers per year: 2024: 1; 2025: 0; 2026: 3.
4 papers.
- 2024Exploring LLM-Driven Explanations for Quantum Algorithmscited by 7
- 2026QBugLM: An Agentic Benchmarking Framework for LLM-based Quantum Software Debuggingcited by 2
- 2026Q-Bridge: Code Translation for Quantum Machine Learning via LLMscited by 1
- 2026Fine-Tuning Large Language Models for Quantum Reasoningcited by 0
- 2026Fine-Tuning Large Language Models for Quantum Reasoning20 Jun 2026
- 2026QBugLM: An Agentic Benchmarking Framework for LLM-based Quantum Software Debugging5 Jun 2026
- 2026Q-Bridge: Code Translation for Quantum Machine Learning via LLMs29 Mar 2026
- 2024Exploring LLM-Driven Explanations for Quantum Algorithms26 Sep 2024