Towards automating precision studies of clone detectors
Abstract
Current research in clone detection suffers from poor ecosystems for evaluating precision of clone detection tools. Corpora of labeled clones are scarce and incomplete, making evaluation labor intensive and idiosyncratic, and limiting intertool comparison. Precision-assessment tools are simply lacking. We present a semiautomated approach to facilitate precision studies of clone detection tools. The approach merges automatic mechanisms of clone classification with manual validation of clone pairs. We demonstrate that the proposed automatic approach has a very high precision and it significantly reduces the number of clone pairs that need human validation during precision experiments. Moreover, we aggregate the individual effort of multiple teams into a single evolving dataset of labeled clone pairs, creating an important asset for software clone research.
BibTeX
@inproceedings{Saini-al:ICSE19,
author = {Vaibhav Saini and
Farima Farmahinifarahani and
Yadong Lu and
Di Yang and
Pedro Martins and
Hitesh Sajnani and
Pierre Baldi and
Cristina V. Lopes},
title = {Towards automating precision studies of clone detectors},
booktitle = {ICSE},
pages = {49--59},
publisher = {{IEEE} / {ACM}},
year = {2019},
}