Testing and Debugging Quantum Programs: The Road to 2030
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Abstract (arXiv)
Quantum computing has existed in the theoretical realm for several decades. Recently, quantum computing has re-emerged as a promising technology to solve problems that a classical computer could take hundreds of years to solve. However, there are challenges and opportunities for academics and practitioners regarding software engineering practices for testing and debugging quantum programs. This paper presents a roadmap for addressing these challenges, pointing out the existing gaps in the literature and suggesting research directions. We discuss the limitations caused by noise, the no-cloning theorem, the lack of a standard architecture for quantum computers, among others. Regarding testing, we highlight gaps and opportunities related to transpilation, mutation analysis, input states with hybrid interfaces, program analysis, and coverage. For debugging, we present the current strategies, including classical techniques applied to quantum programs, quantum-specific assertions, and quantum-related bug patterns. We introduce a conceptual model to illustrate concepts regarding the testing and debugging of quantum programs and the relationship between them. Those concepts are used to identify and discuss research challenges to cope with quantum programs through 2030, focusing on the interfaces between classical and quantum computing and on creating testing and debugging techniques that take advantage of the unique quantum computing characteristics.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 May 2024.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 2.
5 papers.
- 2025QAgent: An LLM-based Multi-Agent System for Autonomous OpenQASM programmingcited by 9
- 2024Exploring LLM-Driven Explanations for Quantum Algorithmscited by 7
- 2025Taxonomy of migration scenarios for Qiskit refactoring using LLMscited by 2
- 2026QBugLM: An Agentic Benchmarking Framework for LLM-based Quantum Software Debuggingcited by 2
- 2026Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scalingcited by 0
- 2026Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scaling15 Jul 2026
- 2026QBugLM: An Agentic Benchmarking Framework for LLM-based Quantum Software Debugging5 Jun 2026
- 2025QAgent: An LLM-based Multi-Agent System for Autonomous OpenQASM programming26 Aug 2025
- 2025Taxonomy of migration scenarios for Qiskit refactoring using LLMs8 Jun 2025
- 2024Exploring LLM-Driven Explanations for Quantum Algorithms26 Sep 2024