README.md

metadata

annotations_creators: []
language_creators:
  - crowdsourced
  - expert-generated
language:
  - code
license:
  - mit
multilinguality:
  - monolingual
pretty_name: CoNaLa
size_categories:
  - unknown
source_datasets:
  - original
task_categories:
  - text2text-generation
task_ids:
  - text2text-generation-other-code-generation

Dataset Description

• Repository: https://conala-corpus.github.io/
• Paper: Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow

Dataset Summary

CoNaLa is a benchmark of code and natural language pairs, for the evaluation of code generation tasks. The dataset was crawled from Stack Overflow, automatically filtered, then curated by annotators, split into 2,379 training and 500 test examples. The automatically mined dataset is also available with almost 600k examples.

Supported Tasks and Leaderboards

This dataset is used to evaluate code generations.

Languages

English - Python code.

Dataset Structure

dataset_curated = load_dataset("neulab/conala")
DatasetDict({
    train: Dataset({
        features: ['question_id', 'intent', 'rewritten_intent', 'snippet'],
        num_rows: 2379
    })
    test: Dataset({
        features: ['question_id', 'intent', 'rewritten_intent', 'snippet'],
        num_rows: 500
    })
})

dataset_mined = load_dataset("neulab/conala", "mined")
DatasetDict({
    train: Dataset({
        features: ['question_id', 'parent_answer_post_id', 'prob', 'snippet', 'intent', 'id'],
        num_rows: 593891
    })
})

Data Instances

CoNaLa - curated

This is the curated dataset by annotators

{
    'question_id': 41067960,
    'intent': 'How to convert a list of multiple integers into a single integer?',
    'rewritten_intent': "Concatenate elements of a list 'x' of multiple integers to a single integer",
    'snippet': 'sum(d * 10 ** i for i, d in enumerate(x[::-1]))'
}

CoNaLa - mined

This is the automatically mined dataset before curation

{
    'question_id': 34705205,
     'parent_answer_post_id': 34705233,
     'prob': 0.8690001442846342,
     'snippet': 'sorted(l, key=lambda x: (-int(x[1]), x[0]))',
     'intent': 'Sort a nested list by two elements',
     'id': '34705205_34705233_0'
}

Data Fields

Curated:

Field	Type	Description
question_id	int64	Id of the Stack Overflow question
intent	string	Natural Language intent (i.e., the title of a Stack Overflow question)
rewritten_intent	string	Crowdsourced revised intents that try to better reflect the full meaning of the code
snippet	string	Code snippet that implements the intent

Mined:

Field	Type	Description
question_id	int64	Id of the Stack Overflow question
parent_answer_post_id	int64	Id of the answer post from which the candidate snippet is extracted
intent	string	Natural Language intent (i.e., the title of a Stack Overflow question)
snippet	string	Code snippet that implements the intent
id	string	Unique id for this intent/snippet pair
prob	float64	Probability given by the mining model

Data Splits

There are two version of the dataset (curated and mined), mined only has a train split and curated has two splits: train and test.

Dataset Creation

The dataset was crawled from Stack Overflow, automatically filtered, then curated by annotators. For more details, please refer to the original paper

Citation Information

@inproceedings{yin2018learning,
  title={Learning to mine aligned code and natural language pairs from stack overflow},
  author={Yin, Pengcheng and Deng, Bowen and Chen, Edgar and Vasilescu, Bogdan and Neubig, Graham},
  booktitle={2018 IEEE/ACM 15th international conference on mining software repositories (MSR)},
  pages={476--486},
  year={2018},
  organization={IEEE}
}