"""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], }