Datasets:
Languages:
code
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
| """The Loyola University of Delaware Identifier Splitting Oracle""" | |
| import datasets | |
| import pandas as pd | |
| from collections import deque | |
| _CITATION = """ | |
| @article{hill2014empirical, | |
| title={An empirical study of identifier splitting techniques}, | |
| author={Hill, Emily and Binkley, David and Lawrie, Dawn and Pollock, Lori and Vijay-Shanker, K}, | |
| journal={Empirical Software Engineering}, | |
| volume={19}, | |
| number={6}, | |
| pages={1754--1780}, | |
| year={2014}, | |
| publisher={Springer} | |
| } | |
| """ | |
| _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. | |
| The Loyola University of Delaware Identifier Splitting Oracle 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/loyola-udelaware-identifier-splitting-oracle.txt" | |
| class Loyola(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"), | |
| "language": datasets.Value("string"), | |
| "source": datasets.Value("string") | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="http://www.cs.loyola.edu/~binkley/ludiso/", | |
| 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="-"): | |
| 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 | |
| output = haystack | |
| while pos: | |
| next_pos = pos.popleft() | |
| output = output[:next_pos] + " " + output[next_pos:] | |
| pos = deque() | |
| previous = output[0] | |
| for index, char in enumerate(output[1:]): | |
| if (not previous.isalnum() and not previous.isspace()) and char.isalnum(): | |
| pos.appendleft(index + 1) | |
| previous = char | |
| while pos: | |
| next_pos = pos.popleft() | |
| output = output[:next_pos] + " " + output[next_pos:] | |
| return output | |
| with open(filepath, 'r') as f: | |
| records = f.read().split("\n") | |
| records = [x for x in records if x] | |
| records = [x.split(" ") for x in records] | |
| for idx, item in enumerate(records): | |
| yield idx, { | |
| "index": idx, | |
| "identifier": item[1], | |
| "segmentation": get_segmentation(item[4], item[1]), | |
| "language": item[2], | |
| "source": item[3], | |
| } |