|
--- |
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language: |
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- en |
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license: mit |
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size_categories: |
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- n<1K |
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task_categories: |
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- text2text-generation |
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pretty_name: ClassEval |
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tags: |
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- code-generation |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: data/test-* |
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dataset_info: |
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features: |
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- name: task_id |
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dtype: string |
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- name: skeleton |
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dtype: string |
|
- name: test |
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dtype: string |
|
- name: solution_code |
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dtype: string |
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- name: import_statement |
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sequence: string |
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- name: class_description |
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dtype: string |
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- name: methods_info |
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list: |
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- name: method_name |
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dtype: string |
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- name: method_description |
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dtype: string |
|
- name: test_class |
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dtype: string |
|
- name: test_code |
|
dtype: string |
|
- name: solution_code |
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dtype: string |
|
- name: dependencies |
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struct: |
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- name: Standalone |
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dtype: bool |
|
- name: lib_dependencies |
|
sequence: string |
|
- name: field_dependencies |
|
sequence: string |
|
- name: method_dependencies |
|
sequence: string |
|
- name: class_name |
|
dtype: string |
|
- name: test_classes |
|
sequence: string |
|
- name: class_constructor |
|
dtype: string |
|
- name: fields |
|
sequence: string |
|
splits: |
|
- name: test |
|
num_bytes: 2045743 |
|
num_examples: 100 |
|
download_size: 504216 |
|
dataset_size: 2045743 |
|
--- |
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|
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# Dataset Card for FudanSELab ClassEval |
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## Dataset Description |
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- **Repository:** [GitHub Repository](https://github.com/FudanSELab/ClassEval) |
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- **Paper:** [ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation](https://arxiv.org/abs/2308.01861) |
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### Dataset Summary |
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We manually build ClassEval of 100 class-level Python coding tasks, consists of 100 classes and 412 methods, and average 33.1 test cases per class. |
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For 100 class-level tasks, diversity is maintained by encompassing these tasks over a wide spectrum of topics, including Management Systems, Data Formatting, Mathematical Operations, Game Development, File Handing, Database Operations and Natural Language Processing. |
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For 412 methods, they have been constructed with diverse dependencies, including (i) Library Dependency, where the methods rely on specific external libraries; (ii) Field Dependency, in which the methods are contingent on class instance variables, or fields; (iii) Method Dependency, where the methods are dependent on other methods within the same class; and (iv) Standalone, wherein the methods operate independently without reliance on fields, other methods, or external libraries. |
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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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|
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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 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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### Source Data |
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Manually-crafted |
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## Additional Information |
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### Licensing Information |
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This repository is under [MIT](https://github.com/FudanSELab/ClassEval/blob/master/LICENSE) license. But the data is distributes through [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) license. |
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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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Xueying Du xueyingdu21@m.fudan.edu.cn |
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Mingwei Liu liumingwei@fudan.edu.cn |
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Kaixin Wang kxwang23@m.fudan.edu.cn |
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Hanlin Wang wanghanlin23@m.fudan.edu.cn |
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Junwei Liu jwliu22@m.fudan.edu.cn |
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Yixuan Chen 23212010005@m.fudan.edu.cn |
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Jiayi Feng 23210240148@m.fudan.edu.cn |
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Chaofeng Sha cfsha@fudan.edu.cn |
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Xin Peng pengxin@fudan.edu.cn |
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Yiling Lou yilinglou@fudan.edu.cn |
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