Failure-guided local fuzzing around non-convergent seeds improves detection of faulty HQC configurations over random testing, with concolic seeding adding workload-dependent benefits on VQE versus QAOA.
Detecting flaky tests in quantum software: A dynamic approach,
2 Pith papers cite this work. Polarity classification is still indexing.
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Bayesian sequential verification reduces measurement costs for quantum programs by updating decisions incrementally using priors from reference runs or ideal simulations, outperforming fixed budgets when success probability exceeds the threshold.
citing papers explorer
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Failure-Guided Fuzzing for Hybrid Quantum-Classical Programs
Failure-guided local fuzzing around non-convergent seeds improves detection of faulty HQC configurations over random testing, with concolic seeding adding workload-dependent benefits on VQE versus QAOA.
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Bayesian Sequential Verification for Budget-Aware Quantum Program Testing
Bayesian sequential verification reduces measurement costs for quantum programs by updating decisions incrementally using priors from reference runs or ideal simulations, outperforming fixed budgets when success probability exceeds the threshold.