Quantum Concolic Testing
Shangzhou Xia, Jianjun Zhao, Fuyuan Zhang, Xiaoyu Guo
Abstract
This paper presents the first concolic testing framework explicitly designed for quantum programs. The framework introduces quantum constraint generation methods for quantum control statements that quantify quantum states and offers a symbolization method for quantum variables. Based on this framework, we generate path constraints for each concrete execution path of a quantum program. These constraints guide the exploration of new paths, with a quantum constraint solver determining outcomes to create novel input samples, thereby enhancing branch coverage. Our framework has been implemented in Python and integrated with Qiskit for practical evaluation. Experimental results show that our concolic testing framework improves branch coverage, generates high-quality quantum input samples, and detects bugs, demonstrating its effectiveness and efficiency in quantum programming and bug detection. Regarding branch coverage, our framework achieves more than 74.27% on quantum programs with under 5 qubits. CCS Concepts: • Software and its engineering → Search-based software engineering.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers1
Ask how each one uses itBuilds on4
- Bugs in Quantum computing platforms: an empirical studyMatteo Paltenghi, Michael PradelOOPSLA 2022 · 70 citations
- MorphQ: Metamorphic Testing of the Qiskit Quantum Computing PlatformMatteo Paltenghi, Michael PradelICSE 2023 · 44 citations
- QuraTest: Integrating Quantum Specific Features in Quantum Program TestingJiaming Ye, Shangzhou Xia, Fuyuan Zhang, Paolo Arcaini et al.ASE 2023 · 19 citations
- Symbolic Execution for Quantum Error Correction ProgramsWang Fang, Mingsheng YingPLDI 2024 · 16 citations
Related papers
- Rare Path Guided FuzzingSeemanta Saha, Laboni Sarker, Md Shafiuzzaman, Chaofan Shou et al.ISSTA 2023 · 12 citations
- Analyzing Quantum Programs with LintQ: A Static Analysis Framework for QiskitMatteo Paltenghi, Michael PradelFSE 2024 · 19 citations
- Cottontail: Large Language Model-Driven Concolic Execution for Highly Structured Test Input GenerationHaoxin Tu, Seongmin Lee, Yuxian Li, Peng Chen et al.S&P 2026 · 22 citations
- Learning-based controlled concurrency testingSuvam Mukherjee, Pantazis Deligiannis, Arpita Biswas, Akash LalOOPSLA 2020 · 20 citations
- FeatMaker: Automated Feature Engineering for Search Strategy of Symbolic ExecutionJaehan Yoon, Sooyoung ChaFSE 2024 · 3 citations
