README.md

---
annotations_creators: 
- crowdsourced
license: other
language_creators:
- crowdsourced
language:
- code
task_categories:
- text-generation
tags:
- code, kotlin, native Android development, curated
size_categories:
- 100K<n<1M
source_datasets: []
pretty_name: iva-kotlin-codeint-clean
task_ids:
- language-modeling
---

# IVA Kotlin GitHub Code Dataset

## Dataset Description

This is the curated IVA Kotlin dataset extracted from GitHub. 
It contains curated Kotlin files gathered with the purpose to train a code generation model.

The dataset consists of 383380 Kotlin code files from GitHub totaling ~542MB of data. 
The [uncurated](https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint) dataset was created from the public GitHub dataset on Google BiqQuery.

### How to use it

To download the full dataset:

```python
from datasets import load_dataset
dataset = load_dataset('mvasiliniuc/iva-kotlin-codeint-clean', split='train')
```


Other details are available for each field:

```python
from datasets import load_dataset
dataset = load_dataset('mvasiliniuc/iva-kotlin-codeint-clean', split='train')
print(dataset[723])

#OUTPUT:
{
   "repo_name":"oboenikui/UnivCoopFeliCaReader",
   "path":"app/src/main/java/com/oboenikui/campusfelica/ScannerActivity.kt",
   "copies":"1",
   "size":"5635",
   "content":"....public override fun onPause() {\n        if (this.isFinishing) {\n            adapter.disableForegroundDispatch(this)\n        }\n        super.onPause()\n    }\n\n    override ...}\n",
   "license":"apache-2.0",
   "hash":"e88cfd99346cbef640fc540aac3bf20b",
   "line_mean":37.8620689655,
   "line_max":199,
   "alpha_frac":0.5724933452,
   "ratio":5.0222816399,
   "autogenerated":false,
   "config_or_test":false,
   "has_no_keywords":false,
   "has_few_assignments":false
}
```

## Data Structure

### Data Fields

|Field|Type|Description|
|---|---|---|
|repo_name|string|name of the GitHub repository|
|path|string|path of the file in GitHub repository|
|copies|string|number of occurrences in dataset|
|content|string|content of source file|
|size|string|size of the source file in bytes|
|license|string|license of GitHub repository|
|hash|string|Hash of content field.|
|line_mean|number|Mean line length of the content.
|line_max|number|Max line length of the content.
|alpha_frac|number|Fraction between mean and max line length of content.
|ratio|number|Character/token ratio of the file with tokenizer.
|autogenerated|boolean|True if the content is autogenerated by looking for keywords in the first few lines of the file.
|config_or_test|boolean|True if the content is a configuration file or a unit test.
|has_no_keywords|boolean|True if a file has none of the keywords for Kotlin Programming Language.
|has_few_assignments|boolean|True if file uses symbol '=' less than `minimum` times.

### Instance

```json
{
   "repo_name":"oboenikui/UnivCoopFeliCaReader",
   "path":"app/src/main/java/com/oboenikui/campusfelica/ScannerActivity.kt",
   "copies":"1",
   "size":"5635",
   "content":"....",
   "license":"apache-2.0",
   "hash":"e88cfd99346cbef640fc540aac3bf20b",
   "line_mean":37.8620689655,
   "line_max":199,
   "alpha_frac":0.5724933452,
   "ratio":5.0222816399,
   "autogenerated":false,
   "config_or_test":false,
   "has_no_keywords":false,
   "has_few_assignments":false
}
```

## Languages

The dataset contains only Kotlin files.

```json
{
    "Kotlin": [".kt"]
}
```

## Licenses

Each entry in the dataset contains the associated license. The following is a list of licenses involved and their occurrences.

```json
{
   "agpl-3.0":4052,
   "apache-2.0":114641,
   "artistic-2.0":159,
   "bsd-2-clause":474,
   "bsd-3-clause":4571,
   "cc0-1.0":198,
   "epl-1.0":991,
   "gpl-2.0":5625,
   "gpl-3.0":25102,
   "isc":436,
   "lgpl-2.1":146,
   "lgpl-3.0":3406,
   "mit":39399,
   "mpl-2.0":1819,
   "unlicense":824
}
```

## Dataset Statistics

```json
{
    "Total size": "~261 MB",
    "Number of files": 201843,
    "Number of files under 500 bytes": 3697,
    "Average file size in bytes": 5205,
}
```

## Curation Process

* Removal of duplication files based on file hash.
* Removal of file templates. File containing the following: [${PACKAGE_NAME}, ${NAME}, ${VIEWHOLDER_CLASS}, ${ITEM_CLASS}]
* Removal of the files containing the following words in the first 10 lines: `generated, auto-generated", "autogenerated", "automatically generated`
* Removal of the files containing the following words in the first 10 lines with a probability of 0.7: `test", "unit test", "config", "XCTest", "JUnit`
* Removal of file with the rate of alphanumeric characters below 0.3 of the file.
* Removal of near duplication based MinHash and Jaccard similarity.
* Removal of files with mean line length above 100.
* Removal of files without mention of keywords with a probability of 0.7: [`"fun ", "val ", "var ", "if ", "else ", "while ", "for ", "return ", "class ", "data ", "struct ", "interface ", "when ", "catch "`]
* Removal of files that use the assignment operator `=` less than 3 times.
* Removal of files with the ratio between the number of characters and number of tokens after tokenization lower than 1.5.

Curation process is a derivation of the one used in CodeParrot project: https://huggingface.co/codeparrot

## Data Splits
The dataset only contains a train split which is separated into train and valid which can be found here:
* Clean Version Train: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean-train
* Clean Version Valid: https://huggingface.co/datasets/mvasiliniuc/iva-kotlin-codeint-clean-valid

# Considerations for Using the Data

The dataset comprises source code from various repositories, potentially containing harmful or biased code, 
along with sensitive information such as passwords or usernames.