Datasets:
Languages:
code
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
| """Binkley""" | |
| import datasets | |
| import pandas as pd | |
| from collections import deque | |
| _CITATION = """ | |
| @inproceedings{inproceedings, | |
| author = {Lawrie, Dawn and Binkley, David and Morrell, Christopher}, | |
| year = {2010}, | |
| month = {11}, | |
| pages = {3 - 12}, | |
| title = {Normalizing Source Code Vocabulary}, | |
| journal = {Proceedings - Working Conference on Reverse Engineering, WCRE}, | |
| doi = {10.1109/WCRE.2010.10} | |
| } | |
| """ | |
| _DESCRIPTION = """ | |
| In programming languages, identifiers are tokens (also called symbols) which name language entities. | |
| Some of the kinds of entities an identifier might denote include variables, types, labels, subroutines, and packages. | |
| Binkley is a dataset for identifier segmentation, | |
| i.e. the task of adding spaces between the words on a identifier. | |
| """ | |
| _URL = "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/binkley.csv" | |
| class Binkley(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "index": datasets.Value("int32"), | |
| "identifier": datasets.Value("string"), | |
| "segmentation": datasets.Value("string") | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| downloaded_files = dl_manager.download(_URL) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files}), | |
| ] | |
| def _generate_examples(self, filepath): | |
| def get_segmentation(needle, haystack, sep="-"): | |
| output = haystack | |
| needle = needle.lower() | |
| haystack = haystack.lower() | |
| counter = 0 | |
| pos = deque() | |
| iterator = iter(haystack) | |
| for char in needle: | |
| if char == sep: | |
| pos.appendleft(counter) | |
| continue | |
| while True: | |
| try: | |
| next_char = next(iterator) | |
| counter += 1 | |
| if next_char == char: | |
| break | |
| except StopIteration: | |
| break | |
| while pos: | |
| next_pos = pos.popleft() | |
| output = output[:next_pos] + " " + output[next_pos:] | |
| return output | |
| df = pd.read_csv(filepath, header=None)[[0,1]] | |
| df = df.dropna() | |
| records = df.to_dict("records") | |
| for idx, item in enumerate(records): | |
| yield idx, { | |
| "index": idx, | |
| "identifier": item[0], | |
| "segmentation": get_segmentation(item[1], item[0]) | |
| } |