{"ID":5675308,"CreatedAt":"2026-07-03T01:40:09.565152011Z","UpdatedAt":"2026-07-07T01:06:03.009715918Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.02029","arxiv_id":"2607.02029","title":"Benchmarking Quantum Software Testing with Scalable Quantum Programs","abstract":"Quantum software testing (QST) checks whether quantum programs behave according to their intended specifications. A key requirement for QST research is a benchmark that supports rigorous empirical evaluation on programs that are testable and better reflect current software development practices. However, existing studies heavily rely on small hard-coded or circuit-level benchmarks, while available quantum programs are scattered across repositories without clear selection criteria, which limits fair comparison and systematic reproducibility. To this end, we present Qolumbina, a benchmark infrastructure for controlled QST experiments on scalable quantum programs. Qolumbina curates 40 programs from open-source repositories, turns them into test-ready subjects through systematic selection, refactoring, specifications, test case examples, unit tests, and standardized interfaces. We also propose QST-oriented criteria to characterize quantum programs along functionality, output behavior, development complexity, and quantum-specific execution complexity. Using these criteria, our empirical study shows that Qolumbina covers diverse testing-relevant properties and supports scalability analysis beyond fixed-size circuit benchmarks. Through controlled experiments with two recent QST approaches, we demonstrate the feasibility of using Qolumbina for execution-cost and fault-detection studies, and highlight backend-dependent effects that can influence QST result interpretation.","short_abstract":"Quantum software testing (QST) checks whether quantum programs behave according to their intended specifications. A key requirement for QST research is a benchmark that supports rigorous empirical evaluation on programs that are testable and better reflect current software development practices. However, existing studi...","url_abs":"https://arxiv.org/abs/2607.02029","url_pdf":"https://arxiv.org/pdf/2607.02029v1","authors":"[\"Yuechen Li\",\"Minqi Shao\",\"Xiyuan Li\",\"Jianjun Zhao\",\"Kai-Yuan Cai\"]","published":"2026-07-02T10:56:35Z","proceeding":"cs.SE","tasks":"[\"cs.SE\",\"quant-ph\"]","methods":"[]","has_code":false}