Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: UnicodeDecodeError
Message: 'utf-8' codec can't decode byte 0xa7 in position 19675: invalid start byte
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
return next(iter(self.iter(batch_size=n)))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
for key, example in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
for key, pa_table in self._iter_arrow():
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
for key, pa_table in iterator:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/csv/csv.py", line 188, in _generate_tables
csv_file_reader = pd.read_csv(file, iterator=True, dtype=dtype, **self.config.pd_read_csv_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 73, in wrapper
return function(*args, download_config=download_config, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1199, in xpandas_read_csv
return pd.read_csv(xopen(filepath_or_buffer, "rb", download_config=download_config), **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv
return _read(filepath_or_buffer, kwds)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 620, in _read
parser = TextFileReader(filepath_or_buffer, **kwds)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1620, in __init__
self._engine = self._make_engine(f, self.engine)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/readers.py", line 1898, in _make_engine
return mapping[engine](f, **self.options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 93, in __init__
self._reader = parsers.TextReader(src, **kwds)
File "parsers.pyx", line 574, in pandas._libs.parsers.TextReader.__cinit__
File "parsers.pyx", line 663, in pandas._libs.parsers.TextReader._get_header
File "parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "parsers.pyx", line 2053, in pandas._libs.parsers.raise_parser_error
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa7 in position 19675: invalid start byteNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Check out the documentation for more information.
FNFC: Functional & Non-Functional Requirements Classification Dataset
Link: Hugging Face – FNFC Dataset
Overview
The FNFC dataset is a labeled collection of 7,060 software requirement statements categorized into 14 requirement classes, designed for research and modeling in requirements classification. It was created by refining and re-labeling the Fault-prone SRS Dataset from Kaggle, ensuring high-quality annotations through expert review.
Data Collection & Labeling
The labeling process was carried out by five professionals with expertise in software project leadership, systems analysis, or software requirements engineering:
- 2 experts with over 10 years of experience
- 3 experts with 2–3 years of experience in requirements engineering
Each expert received:
- A questionnaire
- Relevant documentation
- Clear labeling criteria for identifying functional and non-functional requirements
Experts were given 20 days to complete labeling at their own pace. Each record was assigned to one of the following classes:
Classes
- F – Functional Requirements
- A – Availability
- AU – Autonomy
- FT – Fault Tolerance
- LF – Look and Feel
- LL – Legal & Licensing
- M – Maintainability
- O – Inter-Operability
- P – Portability
- PE – Performance
- R – Reliability
- SC – Scalability
- SE – Security
- US – Usability
Dataset Structure
| Field | Description |
|---|---|
id |
Unique record identifier |
requirement |
Requirement statement text |
label |
One of the 14 defined classes |
Purpose
The dataset provides a robust benchmark for:
- Machine learning models for requirements classification
- Natural language processing experiments in software engineering
- Studies comparing classification methods for functional vs. non-functional requirements
Access
The dataset is publicly available:
Hugging Face – FNFC Dataset
Citation
If you use this dataset in academic research, please cite:
@dataset{fnfc_dataset_2025,
title={FNFC: Functional & Non-Functional Requirements Classification Dataset},
author={Mashhad Azad University},
year={2025},
url={https://huggingface.co/datasets/Mashhad-Azad-University/FNFC-Functional_Non-Functional_Classification}
}
## Contact
Created by Mahdi Kabootari & Younes Abdeahad
📬 kabootarimahdi2@gmail.com
📬 abdeahad.y3@gmail.com
📬 e.kheirkhah@gmail.com
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