Dataset Viewer
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
instance_id: string
model_patch: string
model_name_or_path: string
fixed_tests: null
p2p_tests: null
f2p_tests: null
s2p_tests: null
n2p_tests: null
fix_patch_result: struct<passed_count: int64, failed_count: int64, skipped_count: int64, passed_tests: list<item: stri (... 73 chars omitted)
child 0, passed_count: int64
child 1, failed_count: int64
child 2, skipped_count: int64
child 3, passed_tests: list<item: string>
child 0, item: string
child 4, failed_tests: list<item: string>
child 0, item: string
child 5, skipped_tests: list<item: string>
child 0, item: string
test_patch_result: struct<passed_count: int64, failed_count: int64, skipped_count: int64, passed_tests: list<item: stri (... 73 chars omitted)
child 0, passed_count: int64
child 1, failed_count: int64
child 2, skipped_count: int64
child 3, passed_tests: list<item: string>
child 0, item: string
child 4, failed_tests: list<item: string>
child 0, item: string
child 5, skipped_tests: list<item: string>
child 0, item: string
error_msg: string
resolved_issues: list<item: struct<number: int64, title: string, body: string>>
child 0, item: struct<number: int64, title: string, body: string>
child 0, number: int64
child 1, title: string
child 2, body: string
test_patch: string
body: string
title: string
state: string
fix_patch: string
org: string
repo: string
run_result: struct<passed_count: int64, failed_count: int64, skipped_count: int64, passed_tests: list<item: stri (... 73 chars omitted)
child 0, passed_count: int64
child 1, failed_count: int64
child 2, skipped_count: int64
child 3, passed_tests: list<item: string>
child 0, item: string
child 4, failed_tests: list<item: string>
child 0, item: string
child 5, skipped_tests: list<item: string>
child 0, item: string
number: int64
base: struct<label: string, ref: string, sha: string>
child 0, label: string
child 1, ref: string
child 2, sha: string
valid: bool
to
{'org': Value('string'), 'repo': Value('string'), 'number': Value('int64'), 'state': Value('string'), 'title': Value('string'), 'body': Value('string'), 'base': {'label': Value('string'), 'ref': Value('string'), 'sha': Value('string')}, 'resolved_issues': List({'number': Value('int64'), 'title': Value('string'), 'body': Value('string')}), 'fix_patch': Value('string'), 'test_patch': Value('string'), 'valid': Value('bool'), 'error_msg': Value('string'), 'fixed_tests': Json(decode=True), 'p2p_tests': Json(decode=True), 'f2p_tests': Json(decode=True), 's2p_tests': Json(decode=True), 'n2p_tests': Json(decode=True), 'run_result': {'passed_count': Value('int64'), 'failed_count': Value('int64'), 'skipped_count': Value('int64'), 'passed_tests': List(Value('string')), 'failed_tests': List(Value('string')), 'skipped_tests': List(Value('string'))}, 'test_patch_result': {'passed_count': Value('int64'), 'failed_count': Value('int64'), 'skipped_count': Value('int64'), 'passed_tests': List(Value('string')), 'failed_tests': List(Value('string')), 'skipped_tests': List(Value('string'))}, 'fix_patch_result': {'passed_count': Value('int64'), 'failed_count': Value('int64'), 'skipped_count': Value('int64'), 'passed_tests': List(Value('string')), 'failed_tests': List(Value('string')), 'skipped_tests': List(Value('string'))}, 'instance_id': Value('string')}
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 483, 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
instance_id: string
model_patch: string
model_name_or_path: string
fixed_tests: null
p2p_tests: null
f2p_tests: null
s2p_tests: null
n2p_tests: null
fix_patch_result: struct<passed_count: int64, failed_count: int64, skipped_count: int64, passed_tests: list<item: stri (... 73 chars omitted)
child 0, passed_count: int64
child 1, failed_count: int64
child 2, skipped_count: int64
child 3, passed_tests: list<item: string>
child 0, item: string
child 4, failed_tests: list<item: string>
child 0, item: string
child 5, skipped_tests: list<item: string>
child 0, item: string
test_patch_result: struct<passed_count: int64, failed_count: int64, skipped_count: int64, passed_tests: list<item: stri (... 73 chars omitted)
child 0, passed_count: int64
child 1, failed_count: int64
child 2, skipped_count: int64
child 3, passed_tests: list<item: string>
child 0, item: string
child 4, failed_tests: list<item: string>
child 0, item: string
child 5, skipped_tests: list<item: string>
child 0, item: string
error_msg: string
resolved_issues: list<item: struct<number: int64, title: string, body: string>>
child 0, item: struct<number: int64, title: string, body: string>
child 0, number: int64
child 1, title: string
child 2, body: string
test_patch: string
body: string
title: string
state: string
fix_patch: string
org: string
repo: string
run_result: struct<passed_count: int64, failed_count: int64, skipped_count: int64, passed_tests: list<item: stri (... 73 chars omitted)
child 0, passed_count: int64
child 1, failed_count: int64
child 2, skipped_count: int64
child 3, passed_tests: list<item: string>
child 0, item: string
child 4, failed_tests: list<item: string>
child 0, item: string
child 5, skipped_tests: list<item: string>
child 0, item: string
number: int64
base: struct<label: string, ref: string, sha: string>
child 0, label: string
child 1, ref: string
child 2, sha: string
valid: bool
to
{'org': Value('string'), 'repo': Value('string'), 'number': Value('int64'), 'state': Value('string'), 'title': Value('string'), 'body': Value('string'), 'base': {'label': Value('string'), 'ref': Value('string'), 'sha': Value('string')}, 'resolved_issues': List({'number': Value('int64'), 'title': Value('string'), 'body': Value('string')}), 'fix_patch': Value('string'), 'test_patch': Value('string'), 'valid': Value('bool'), 'error_msg': Value('string'), 'fixed_tests': Json(decode=True), 'p2p_tests': Json(decode=True), 'f2p_tests': Json(decode=True), 's2p_tests': Json(decode=True), 'n2p_tests': Json(decode=True), 'run_result': {'passed_count': Value('int64'), 'failed_count': Value('int64'), 'skipped_count': Value('int64'), 'passed_tests': List(Value('string')), 'failed_tests': List(Value('string')), 'skipped_tests': List(Value('string'))}, 'test_patch_result': {'passed_count': Value('int64'), 'failed_count': Value('int64'), 'skipped_count': Value('int64'), 'passed_tests': List(Value('string')), 'failed_tests': List(Value('string')), 'skipped_tests': List(Value('string'))}, 'fix_patch_result': {'passed_count': Value('int64'), 'failed_count': Value('int64'), 'skipped_count': Value('int64'), 'passed_tests': List(Value('string')), 'failed_tests': List(Value('string')), 'skipped_tests': List(Value('string'))}, 'instance_id': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
👋 Overview
NTBench (Non-Termination Benchmark) is a software engineering dataset containing real-world GitHub pull requests associated with non-termination defects, particularly infinite loops and infinite recursion.
Each instance includes issue-resolution information, developer-provided patches, test modifications, categorized test cases, and test execution results before and after applying the patches. The repository also provides the complete agent execution trajectories used in our experiments. NTBench is intended to support research on automated program repair, software engineering agents, issue resolution, and the diagnosis and repair of non-termination defects. Generated patches, evaluator logs, processed results, review records, and data-processing scripts are available in the companion GitHub repository. The executable Docker images are available on Docker Hub.
⚙️ Usage
# Make sure git-lfs is installed (https://git-lfs.com)
git lfs install
git clone https://huggingface.co/datasets/liheng520/NTBench
cd NTBench
unzip traj.zip -d trajectories
🧩 Data Instance Structure
Each NTBench instance contains the following fields:
org: (str) - The GitHub organization or repository owner.
repo: (str) - The GitHub repository name.
number: (int) - The pull request number.
state: (str) - The state of the pull request.
title: (str) - The title of the pull request.
body: (str) - The body of the pull request.
base: (dict) - Information about the target branch or base revision of the pull request.
resolved_issues: (list) - A list of issues associated with and resolved by the pull request.
fix_patch: (str) - The source-code patch contributed by the solution pull request.
test_patch: (str) - The test patch associated with the pull request.
fixed_tests: (dict) - Tests identified as relevant to the issue resolution.
p2p_tests: (dict) - Pass-to-Pass tests that pass both before and after applying the fix.
f2p_tests: (dict) - Fail-to-Pass tests that fail before the fix and pass after applying the fix.
s2p_tests: (dict) - Skip-to-Pass tests that are skipped before the fix and pass after applying the fix.
n2p_tests: (dict) - New-to-Pass tests that do not exist before the pull request and pass after applying the corresponding patches.
run_result: (dict) - Overall test execution results, including the numbers of passed and failed tests.
test_patch_result: (dict) - Test execution results after applying the test patch.
fix_patch_result: (dict) - Test execution results after applying both the test patch and the fix patch.
instance_id: (str) - A unique instance identifier, typically formatted as org__repo_PR-number.
📜 License
The dataset contains metadata, patches, issue information, and test information derived from multiple public GitHub repositories. The original source code and repository contents remain subject to the licenses of their respective upstream projects.
Please consult the license of each original repository before redistributing or reusing repository-derived content. Additional annotations introduced by NTBench are released under the terms specified by this dataset repository.
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