SinkFinder: harvesting hundreds of unknown interesting function pairs with just one seed
Abstract
Mastering the knowledge about security-sensitive functions that can potentially result in bugs is valuable to detect them. However, identifying this kind of functions is not a trivial task. Introducing machine learning-based techniques to do the task is a natural choice. Unfortunately, the approach also requires considerable prior knowledge, e.g., sufficient labelled training samples. In practice, the requirement is often hard to meet.
BibTeX
@inproceedings{Bian-al:FSE20,
author = {Pan Bian and
Bin Liang and
Jianjun Huang and
Wenchang Shi and
Xidong Wang and
Jian Zhang},
title = {{SinkFinder:} harvesting hundreds of unknown interesting function pairs with just one seed},
booktitle = {{ESEC/SIGSOFT} {FSE}},
pages = {1101--1113},
publisher = {{ACM}},
year = {2020},
}