Data quality matters: A case study on data label correctness for security bug report prediction

Data quality matters: A case study on data label correctness for security bug report prediction

In the research of mining software repositories, we need to label a large amount of data to construct a predictive model. The correctness of the labels will affect the performance of a model substantially. However, limited studies have been performed to investigate the impact of mislabeled instances...

Full description

Saved in:
Bibliographic Details
Main Authors: WU, Xiaoxue, ZHENG, Wei, XIA, Xin, LO, David
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
Computer bugs
Noise measurement
Predictive models
Security
Chromium
Tuning
Data models
Security bug report prediction
data quality
label correctness
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/7436
https://ink.library.smu.edu.sg/context/sis_research/article/8439/viewcontent/DataQualityMatters_2022_av.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/7436
https://ink.library.smu.edu.sg/context/sis_research/article/8439/viewcontent/DataQualityMatters_2022_av.pdf

Similar Items