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license: apache-2.0
language:
- en
pretty_name: Quantum API Drift
size_categories:
- n<1K
source_datasets:
- extended
task_categories:
- text-generation
tags:
- code
- code-generation
- benchmark
- quantum-computing
- qiskit
- api-drift
configs:
- config_name: benchmark
default: true
data_files:
- split: test
path: data/benchmark.jsonl
- config_name: version_anchored
data_files:
- split: test
path: data/version_anchored.jsonl
---
# Quantum API Drift
Quantum API Drift is an evaluation benchmark for measuring whether
LLM-generated quantum code targets the requested Qiskit SDK version. It
accompanies the paper
[Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK Versions](https://huggingface.co/papers/2607.04072).
The benchmark evaluates version fidelity, cross-version compatibility, failure
modes, and documentation-guided repair across Qiskit 0.43, 1.3, and 2.0.
## Dataset Configurations
### benchmark
The default configuration contains 50 evaluation tasks. Each row has:
- `id`: the upstream Qiskit HumanEval task identifier
- `description`: the natural-language coding task
- `entry_point`: the function the generated code must define
- `test_call`: executable assertions used by the benchmark harness
Load it with:
```python
from datasets import load_dataset
dataset = load_dataset("arasyi/quantum-api-drift")
tasks = dataset["test"]
```
### version_anchored
This configuration contains 150 prompts: one prompt for each combination of 50
tasks and three requested SDK versions. Each row has:
- `id`: the source task identifier
- `version`: `v0`, `v1`, or `v2`
- `entry_point`: the required function name
- `test_call`: executable assertions
- `prompt`: the complete SDK-version-anchored generation prompt
The version labels map to Qiskit releases as follows:
| Label | Qiskit version |
|---|---:|
| `v0` | 0.43 |
| `v1` | 1.3 |
| `v2` | 2.0 |
Load it with:
```python
from datasets import load_dataset
dataset = load_dataset(
"arasyi/quantum-api-drift",
"version_anchored",
)
prompts = dataset["test"]
```
## Auxiliary Files
The `migration_notes/` directory contains the migration guidance used by the
documentation-guided repair experiments:
- `v0_to_v1.txt`: Qiskit 0.43 to 1.3
- `v1_to_v2.txt`: Qiskit 1.3 to 2.0
These files are research artifacts and are not loaded as dataset rows.
## Source and Modifications
The task descriptions and identifiers are derived from the
[Qiskit HumanEval dataset](https://huggingface.co/datasets/Qiskit/qiskit_humaneval)
and its [source repository](https://github.com/qiskit-community/qiskit-human-eval),
which are distributed under the Apache License 2.0.
Quantum API Drift modifies the upstream material by selecting 50 tasks,
adapting executable test calls for cross-version evaluation, and constructing
SDK-version-specific prompts. The modification and attribution notice is also
provided in `NOTICE`.
## Intended Use
This dataset is intended for evaluating version-aware quantum code generation,
cross-version execution compatibility, API-drift failure modes, and
documentation-guided repair. All rows are evaluation data and are published in
the `test` split; they should not be presented as a training split.
## Limitations
- The benchmark measures API-level and execution-level validity, not full
semantic circuit correctness.
- Results depend on the execution environment and pinned Qiskit versions.
- Repair results depend on the supplied migration notes.
- The source benchmark and this derivative are public, so evaluations should
discuss possible benchmark contamination.
- Model generations, execution traces, and aggregate paper results are not
included in this dataset repository.
## License
The dataset is distributed under the Apache License 2.0. See `LICENSE` and
`NOTICE` for the complete terms and attribution.
## Citation
```bibtex
@misc{rasyidi2026benchmarkingapidrift,
title={Benchmarking API Drift in LLM-Generated Quantum Code Across Successive SDK Versions},
author={Rasyidi, Mohammad Arif and Faiz, Syahirul},
year={2026},
eprint={2607.04072},
archivePrefix={arXiv},
primaryClass={cs.SE},
doi={10.48550/arXiv.2607.04072},
url={https://arxiv.org/abs/2607.04072}
}
```
When reusing the underlying tasks, also cite the
[Qiskit HumanEval project](https://github.com/qiskit-community/qiskit-human-eval).
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