Datasets:

google
/

code_x_glue_cc_code_to_code_trans

	---
	annotations_creators:
	- expert-generated
	language_creators:
	- found
	languages:
	- code
	licenses:
	- other-C-UDA
	multilinguality:
	- other-programming-languages
	size_categories:
	- 10K<n<100K
	source_datasets:
	- original
	task_categories:
	- translation
	task_ids:
	- translation-other-code-to-code
	pretty_name: CodeXGlueCcCodeToCodeTrans
	---
	# Dataset Card for "code_x_glue_cc_code_to_code_trans"

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits-sample-size)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans

	### Dataset Summary

	CodeXGLUE code-to-code-trans dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Code-Code/code-to-code-trans

	The dataset is collected from several public repos, including Lucene(http://lucene.apache.org/), POI(http://poi.apache.org/), JGit(https://github.com/eclipse/jgit/) and Antlr(https://github.com/antlr/).
	We collect both the Java and C# versions of the codes and find the parallel functions. After removing duplicates and functions with the empty body, we split the whole dataset into training, validation and test sets.

	### Supported Tasks and Leaderboards

	- `machine-translation`: The dataset can be used to train a model for translating code in Java to C# and vice versa.

	### Languages

	- Java programming language
	- C# programming language

	## Dataset Structure

	### Data Instances

	An example of 'validation' looks as follows.
	```
	{
	"cs": "public DVRecord(RecordInputStream in1){_option_flags = in1.ReadInt();_promptTitle = ReadUnicodeString(in1);_errorTitle = ReadUnicodeString(in1);_promptText = ReadUnicodeString(in1);_errorText = ReadUnicodeString(in1);int field_size_first_formula = in1.ReadUShort();_not_used_1 = in1.ReadShort();_formula1 = NPOI.SS.Formula.Formula.Read(field_size_first_formula, in1);int field_size_sec_formula = in1.ReadUShort();_not_used_2 = in1.ReadShort();_formula2 = NPOI.SS.Formula.Formula.Read(field_size_sec_formula, in1);_regions = new CellRangeAddressList(in1);}\n",
	"id": 0,
	"java": "public DVRecord(RecordInputStream in) {_option_flags = in.readInt();_promptTitle = readUnicodeString(in);_errorTitle = readUnicodeString(in);_promptText = readUnicodeString(in);_errorText = readUnicodeString(in);int field_size_first_formula = in.readUShort();_not_used_1 = in.readShort();_formula1 = Formula.read(field_size_first_formula, in);int field_size_sec_formula = in.readUShort();_not_used_2 = in.readShort();_formula2 = Formula.read(field_size_sec_formula, in);_regions = new CellRangeAddressList(in);}\n"
	}
	```

	### Data Fields

	In the following each data field in go is explained for each config. The data fields are the same among all splits.

	#### default

	\|field name\| type \| description \|
	\|----------\|------\|-----------------------------\|
	\|id \|int32 \| Index of the sample \|
	\|java \|string\| The java version of the code\|
	\|cs \|string\| The C# version of the code \|

	### Data Splits

	\| name \|train\|validation\|test\|
	\|-------\|----:\|---------:\|---:\|
	\|default\|10300\| 500\|1000\|

	## Dataset Creation

	### Curation Rationale

	[More Information Needed]

	### Source Data

	#### Initial Data Collection and Normalization

	[More Information Needed]

	#### Who are the source language producers?

	[More Information Needed]

	### Annotations

	#### Annotation process

	[More Information Needed]

	#### Who are the annotators?

	[More Information Needed]

	### Personal and Sensitive Information

	[More Information Needed]

	## Considerations for Using the Data

	### Social Impact of Dataset

	[More Information Needed]

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	[More Information Needed]

	## Additional Information

	### Dataset Curators

	https://github.com/microsoft, https://github.com/madlag

	### Licensing Information

	Computational Use of Data Agreement (C-UDA) License.

	### Citation Information

	```
	@article{CodeXGLUE,
	title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
	year={2020},}
	```

	### Contributions

	Thanks to @madlag (and partly also @ncoop57) for adding this dataset.