arXiv:2607.04072v1 Announce Type: cross Abstract: Large language models can generate plausible quantum code, but it is unclear whether they can reliably target the specific software development kit (SDK) version requested by the user. We study this problem as API drift and introduce quantum-api-drift, a benchmark for measuring version fidelity, defined here as execution success on the requested SDK version, cross-version compatibility, failure modes, and documentation-guided repair in LLM-generated quantum SDK code. We instantiate the benchmark with Qiskit, a representative quantum SDK that un
The proliferation of LLMs capable of code generation necessitates robust benchmarking to ensure their reliability and target fidelity, especially as quantum computing advances.
Reliable LLM-generated code is critical for accelerating quantum software development, but API drift and versioning issues could significantly hinder adoption and introduce vulnerabilities.
This benchmark introduces a standardized method for evaluating LLM performance in generating quantum code that adheres to specific SDK versions, revealing a clear area for improvement in agentic systems.
- · Quantum SDK developers
- · LLM developers investing in code generation accuracy
- · Quantum computing researchers
- · LLMs with poor version fidelity
- · Developers relying on unvalidated LLM-generated quantum code
- · Quantum projects experiencing API drift issues
Increased focus on LLM fine-tuning and retrieval-augmented generation for version-specific code generation.
Demand for new tooling and methodologies to ensure 'version fidelity' in LLM-generated code across all programming domains, not just quantum.
Potential for an 'AI agent' specialized in identifying and correcting API drift across complex software ecosystems, improving overall code robustness.
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Read at arXiv cs.AI