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Datasets:
fuzzer-app
/
app-gui-ux

Tasks:
Tabular Regression
Languages:
Arabic
English
Tags:
notablly
uxray
ui-ux
telemetry
deterministic
License:
Dataset card Files
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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
ts: timestamp[s]
ux_score: double
low_contrast: int64
accents: int64
tokens_saved_vs_retina: string
model: string
small_targets: int64
accent_colors: list<item: string>
  child 0, item: string
nodes: int64
low_contrast_count: int64
bundle: string
est_vision_tokens_if_ai: int64
n_states: int64
to
{'ts': Value('timestamp[s]'), 'bundle': Value('string'), 'n_states': Value('int64'), 'accent_colors': List(Value('string')), 'low_contrast_count': Value('int64'), 'small_targets': Value('int64'), 'nodes': Value('int64'), 'ux_score': Value('float64'), 'model': Value('string'), 'est_vision_tokens_if_ai': Value('int64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                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 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              ts: timestamp[s]
              ux_score: double
              low_contrast: int64
              accents: int64
              tokens_saved_vs_retina: string
              model: string
              small_targets: int64
              accent_colors: list<item: string>
                child 0, item: string
              nodes: int64
              low_contrast_count: int64
              bundle: string
              est_vision_tokens_if_ai: int64
              n_states: int64
              to
              {'ts': Value('timestamp[s]'), 'bundle': Value('string'), 'n_states': Value('int64'), 'accent_colors': List(Value('string')), 'low_contrast_count': Value('int64'), 'small_targets': Value('int64'), 'nodes': Value('int64'), 'ux_score': Value('float64'), 'model': Value('string'), 'est_vision_tokens_if_ai': Value('int64')}
              because column names don't match

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app-gui-ux — deterministic UI/UX review telemetry

Structured UX-analysis rows emitted by the uxray review engine over app GUI states — a deterministic (non-AI) pass that scores each captured screen bundle.

Schema (app-gui-ux.jsonl, one row per review)

ts, bundle, n_states, accent_colors[], low_contrast_count, small_targets, nodes, ux_score (0–100), model (none-deterministic), est_vision_tokens_if_ai (what a vision-model pass would have cost). runs.jsonl = per-run index.

Use

Feeds the uxray HuggingFace dataset / UX-scoring flywheel: cheap deterministic signals (contrast, target size, node count) that gate whether an expensive AI vision review is warranted. Arabic/RTL layouts are first-class in the source app.
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