CoNaLa Dataset

About this Dataset

The CMU CoNaLa, the Code/Natural Language Challenge dataset is a joint project from the Carnegie Mellon University NeuLab and Strudel labs. Its purpose is for testing the generation of code snippets from natural language. The data comes from StackOverflow questions. There are 2379 training and 500 test examples that were manually annotated. Every example has a natural language intent and its corresponding python snippet. In addition to the manually annotated dataset, there are also 598,237 mined intent-snippet pairs. These examples are similar to the hand-annotated ones except that they contain a probability if the pair is valid.

Source: CoNaLa dataset Homepage

Source: Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow

Dataset Variants

CoNaLa

Papers1

Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow

A novel method to mine high-quality aligned data from SO using two sets of features: hand-crafted features considering the structure of the extracted snippets, and correspondence features obtained by training a probabilistic model to capture the correlation between NL and code using neural networks.

Tasks

EDIT

Code Generation Code Search

Similar Datasets

CoNaLa

CoNaLa

Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow

GLUE

MultiNLI

Penn Treebank