[Paper Contribution]: ProRLearn: boosting prompt tuning-based vulnerability detection by reinforcement learning

[ananyasaha173]

BibTex entry

@Article{Ren2024,
author = {Ren, Zilong and Ju, Xiaolin and Chen, Xiang and Shen, Hao},
title = {ProRLearn: boosting prompt tuning-based vulnerability detection by reinforcement learning},
year = {2024},
journal = {Automated Software Engineering},
volume = {31},
number = {2},
doi = {10.1007/s10515-024-00438-9},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190792140&doi=10.1007%2fs10515-024-00438-9&partnerID=40&md5=7d55632748c15f6d40746f52eb1df703},
type = {Article},
publication_stage = {Final},
source = {Scopus},
note = {Cited by: 0; All Open Access, Green Open Access}
}

Artifacts

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190792140&doi=10.1007%2fs10515-024-00438-9&partnerID=40&md5=7d55632748c15f6d40746f52eb1df703

Tasks

Vulnerability Detection

Models

FFMPeg+Qemu
Reveal
Big-Vul
Sysevr
VulDeePecker
IVDetect
Devign
AMPLE
LineVul