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QEVOLVE-Bench introduces a critical seed artifact for evaluating automated repair strategies as quantum software stacks rapidly evolve. By providing controlled migration tasks across major SDKs like Qiskit and PennyLane, it enables researchers to study how LLMs and agents can maintain quantum program integrity despite breaking changes in execution helpers and device interfaces. This benchmark lowers the barrier to entry for systematic research into the maintenance lifecycle of quantum applications.
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QEVOLVE-Bench: A Seed Benchmark for Quantum SDK Evolution and Repair Planning

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2609.29492v1 Announce Type: new Abstract: Quantum software is increasingly built on fast-moving Python SDKs such as Qiskit, PennyLane, and Cirq. When these SDKs evolve, user programs can fail because execution helpers are removed, import paths change, simulator abstractions shift, device names are deprecated, or circuit export interfaces are revised. Although some failures surface as simple missing-symbol errors, repairing them is not only a syntactic problem: developers must identify the replacement workflow, preserve the quantum-facing intent, and validate behavior under pinned framework versions. This paper presents QEVOLVE-Bench, a small executable seed benchmark for quantum SDK evolution. The current public release contains 14 controlled migration tasks across Qiskit, PennyLane, and Cirq. Each task is a self-contained Python project with pinned dependencies, failing and passing outputs, pytest acceptance checks, metadata, and benchmark notes. The artifact also includes a manifest, sanity checker, representative smoke-test logs, Zenodo archive, screencast, and a lightweight QEVOLVE-Agent prototype that converts task evidence into structured repair proposals. QEVOLVE-Bench is intentionally not a statistically powered benchmark; instead, it is an extensible seed artifact that lowers the setup cost for studying automated repair, LLM-based software engineering, and maintenance of quantum SDK-based projects.

Abstract:Quantum software is increasingly built on fast-moving Python SDKs such as Qiskit, PennyLane, and Cirq. When these SDKs evolve, user programs can fail because execution helpers are removed, import paths change, simulator abstractions shift, device names are deprecated, or circuit export interfaces are revised. Although some failures surface as simple missing-symbol errors, repairing them is not only a syntactic problem: developers must identify the replacement workflow, preserve the quantum-facing intent, and validate behavior under pinned framework versions. This paper presents QEVOLVE-Bench, a small executable seed benchmark for quantum SDK evolution. The current public release contains 14 controlled migration tasks across Qiskit, PennyLane, and Cirq. Each task is a self-contained Python project with pinned dependencies, failing and passing outputs, pytest acceptance checks, metadata, and benchmark notes. The artifact also includes a manifest, sanity checker, representative smoke-test logs, Zenodo archive, screencast, and a lightweight QEVOLVE-Agent prototype that converts task evidence into structured repair proposals. QEVOLVE-Bench is intentionally not a statistically powered benchmark; instead, it is an extensible seed artifact that lowers the setup cost for studying automated repair, LLM-based software engineering, and maintenance of quantum SDK-based projects.

4 pages, 1 figure. Accepted at the 6th International Workshop on Quantum Software Engineering and Technology (Q-SET 2026), IEEE Quantum Week (QCE 2026), Toronto, Canada

arXiv:2609.29492 [quant-ph]

(or arXiv:2609.29492v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.29492 arXiv-issued DOI via DataCite (pending registration)

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