Datasets:
Tasks:
Text2Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
< 1K
ArXiv:
Tags:
code-generation
License:
Commit
•
772c997
1
Parent(s):
0933537
Update README.md
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README.md
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### Languages
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## Dataset Structure
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### Data Instances
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[More Information Needed]
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### Data Fields
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### Data Splits
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## Dataset Creation
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### Citation Information
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### Contributions
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### Languages
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The programming language is Python. The natural language used in the comments and docstrings is English.
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## Dataset Structure
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```python
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from datasets import load_dataset
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dataset = load_dataset("FudanSELab/ClassEval")
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DatasetDict({
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test: Dataset({
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features: ['task_id', 'skeleton', 'test', 'solution_code', 'import_statement', 'class_description', 'methods_info',
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'class_name', 'test_classes', 'class_constructor', 'fields'],
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num_rows: 100
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})
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})
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```
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### Data Instances
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[More Information Needed]
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### Data Fields
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The specific data fields for each task are delineated as follows:
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* task_id: the unique identifier for each task.
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* skeleton: the class skeleton, including all input descriptions in our class-level coding tasks.
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* test: all test cases for the whole class.
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* solution_code: the ground-truth class-level code for each task.
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More fine-grained class-level information from the class skeleton, including:
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* import_statement: the import statements for each task.
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* class_name: the name of the class.
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* class_description: a concise description of the purpose and functionality of the class.
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* class_constructor: the whole constructor of the class.
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* fields: the fields defined in the class_constructor.
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Detailed information for each method in the "methods_info" field, including:
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* method_name: the method signature.
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* method_input: the method contract design, including all input descriptions in the method.
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* test_code: the test cases for the method.
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* solution_code: the ground-truth method-level code.
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* dependencies: the dependency information of the method.
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### Data Splits
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The dataset only consists of a test split with 100 samples.
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## Dataset Creation
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### Citation Information
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```
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@misc{du2023classeval,
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title={ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation},
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author={Xueying Du and Mingwei Liu and Kaixin Wang and Hanlin Wang and Junwei Liu and Yixuan Chen and Jiayi Feng and Chaofeng Sha and Xin Peng and Yiling Lou},
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year={2023},
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eprint={2308.01861},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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### Contributions
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