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amayuelas
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qcurious-tester

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Text Generation

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xet

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train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
n_rounds: int64
results: list<item: struct<module: string, S=1: struct<final: int64, executions: int64, branch_curve: list<it (... 171 chars omitted)
  child 0, item: struct<module: string, S=1: struct<final: int64, executions: int64, branch_curve: list<item: int64>> (... 159 chars omitted)
      child 0, module: string
      child 1, S=1: struct<final: int64, executions: int64, branch_curve: list<item: int64>>
          child 0, final: int64
          child 1, executions: int64
          child 2, branch_curve: list<item: int64>
              child 0, item: int64
      child 2, S=3: struct<final: int64, executions: int64, branch_curve: list<item: int64>>
          child 0, final: int64
          child 1, executions: int64
          child 2, branch_curve: list<item: int64>
              child 0, item: int64
      child 3, S=5: struct<final: int64, executions: int64, branch_curve: list<item: int64>>
          child 0, final: int64
          child 1, executions: int64
          child 2, branch_curve: list<item: int64>
              child 0, item: int64
cost: struct<model: string, api_calls: int64, input_tokens: int64, output_tokens: int64, total_tokens: int (... 157 chars omitted)
  child 0, model: string
  child 1, api_calls: int64
  child 2, input_tokens: int64
  child 3, output_tokens: int64
  child 4, total_tokens: int64
  child 5, total_cost_usd: double
  child 6, per_model: struct<gemini-3-flash-preview: struct<api_calls: int64, input_tokens: int64, output_tokens: int64, c (... 17 chars omitted)
      child 0, gemini-3-flash-preview: struct<api_calls: int64, input_tokens: int64, output_tokens: int64, cost_usd: double>
          child 0, api_calls: int64
          child 1, input_tokens: int64
          child 2, output_tokens: int64
          child 3, cost_usd: double
ablation: string
elapsed: double
to
{'ablation': Value('string'), 'results': List({'module': Value('string'), 'K': Value('int64'), 'random': {'final': Value('int64'), 'branch_curve': List(Value('int64'))}, 'cov_qvalue': {'final': Value('int64'), 'branch_curve': List(Value('int64'))}}), 'cost': {'model': Value('string'), 'api_calls': Value('int64'), 'input_tokens': Value('int64'), 'output_tokens': Value('int64'), 'total_tokens': Value('int64'), 'total_cost_usd': Value('float64'), 'per_model': {'gemini-3-flash-preview': {'api_calls': Value('int64'), 'input_tokens': Value('int64'), 'output_tokens': Value('int64'), 'cost_usd': Value('float64')}}}, 'elapsed': Value('float64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 289, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 124, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              n_rounds: int64
              results: list<item: struct<module: string, S=1: struct<final: int64, executions: int64, branch_curve: list<it (... 171 chars omitted)
                child 0, item: struct<module: string, S=1: struct<final: int64, executions: int64, branch_curve: list<item: int64>> (... 159 chars omitted)
                    child 0, module: string
                    child 1, S=1: struct<final: int64, executions: int64, branch_curve: list<item: int64>>
                        child 0, final: int64
                        child 1, executions: int64
                        child 2, branch_curve: list<item: int64>
                            child 0, item: int64
                    child 2, S=3: struct<final: int64, executions: int64, branch_curve: list<item: int64>>
                        child 0, final: int64
                        child 1, executions: int64
                        child 2, branch_curve: list<item: int64>
                            child 0, item: int64
                    child 3, S=5: struct<final: int64, executions: int64, branch_curve: list<item: int64>>
                        child 0, final: int64
                        child 1, executions: int64
                        child 2, branch_curve: list<item: int64>
                            child 0, item: int64
              cost: struct<model: string, api_calls: int64, input_tokens: int64, output_tokens: int64, total_tokens: int (... 157 chars omitted)
                child 0, model: string
                child 1, api_calls: int64
                child 2, input_tokens: int64
                child 3, output_tokens: int64
                child 4, total_tokens: int64
                child 5, total_cost_usd: double
                child 6, per_model: struct<gemini-3-flash-preview: struct<api_calls: int64, input_tokens: int64, output_tokens: int64, c (... 17 chars omitted)
                    child 0, gemini-3-flash-preview: struct<api_calls: int64, input_tokens: int64, output_tokens: int64, cost_usd: double>
                        child 0, api_calls: int64
                        child 1, input_tokens: int64
                        child 2, output_tokens: int64
                        child 3, cost_usd: double
              ablation: string
              elapsed: double
              to
              {'ablation': Value('string'), 'results': List({'module': Value('string'), 'K': Value('int64'), 'random': {'final': Value('int64'), 'branch_curve': List(Value('int64'))}, 'cov_qvalue': {'final': Value('int64'), 'branch_curve': List(Value('int64'))}}), 'cost': {'model': Value('string'), 'api_calls': Value('int64'), 'input_tokens': Value('int64'), 'output_tokens': Value('int64'), 'total_tokens': Value('int64'), 'total_cost_usd': Value('float64'), 'per_model': {'gemini-3-flash-preview': {'api_calls': Value('int64'), 'input_tokens': Value('int64'), 'output_tokens': Value('int64'), 'cost_usd': Value('float64')}}}, 'elapsed': Value('float64')}
              because column names don't match

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Planning to Explore: Experiment Results

Raw experiment results for the paper "Planning to Explore: Curiosity-Driven Planning for LLM Test Generation".

These JSON files contain all data needed to reproduce the figures and tables in the paper.

Usage

# Clone the code repository
git clone https://github.com/amayuelas/planning-to-explore.git
cd planning-to-explore

# Download results
python scripts/download_results.py

# Regenerate figures
python plots/paper_figures.py
python plots/paper_ablations.py

File Structure

repo_explore_bench/
  full_run_{gemini,gpt54mini,mistral}.json    # Main results (Table 1, Figures 2-5)
  exec_selection_{gemini,gpt54mini,mistral}.json  # Execution-based selection (Appendix)
testgeneval/
  full_run_{gemini,gpt54mini,mistral}.json    # Main results (Table 1, Figures 2-5)
  exec_selection_{gemini,gpt54mini,mistral}.json  # Execution-based selection (Appendix)
ablations/
  ablation_exec_budget.json                   # Figure 6a
  ablation_S_matched.json                     # Figure 6b
  ablation_gamma.json                         # Figure 6c (top)
  ablation_K_plans.json                       # Figure 6c (top)
  ablation_diversity.json                     # Figure 6c (bottom)
  ablation_S_plan_length.json                 # Figure 6b (extended)

Benchmarks

RepoExploreBench (93 targets, 9 repos): click, requests, flask, rich, jinja2, httpx, pydantic, werkzeug, starlette
TestGenEval Lite (140 targets, 11 repos): from SWE-bench

Models

Gemini 3 Flash (Google)
GPT-5.4 Mini (OpenAI)
Mistral Large 3 (Mistral AI)

Citation

@inproceedings{amayuelas2026planning,
  title={Planning to Explore: Curiosity-Driven Planning for LLM Test Generation},
  author={Amayuelas, Alfonso and Laakom, Firas and Pi\k{e}kos, Piotr and Wang, Wenyi and Xu, Yifan and Wang, Yuhui and Schmidhuber, J\"urgen and Wang, William},
  booktitle={Conference on Language Modeling (COLM)},
  year={2026}
}

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