Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Noisy Label Learning for Security Defects   Data-driven software engineering processes, such as vulnerability prediction
heavily rely on the quality of the data used. In this paper, we observe that it
is infeasible to obtain a noise-free security defect dataset in practice.
Despite the vulnerable class, the non-vulnerable modules are difficult to be
verified and determined as truly exploit free given the limited manual efforts
available. It results in uncertainty, introduces labeling noise in the datasets
and affects conclusion validity. To address this issue, we propose novel
learning methods that are robust to label impurities and can leverage the most
from limited label data; noisy label learning. We investigate various noisy
label learning methods applied to software vulnerability prediction.
Specifically, we propose a two-stage learning method based on noise cleaning to
identify and remediate the noisy samples, which improves AUC and recall of
baselines by up to 8.9% and 23.4%, respectively. Moreover, we discuss several
hurdles in terms of achieving a performance upper bound with semi-omniscient
knowledge of the label noise. Overall, the experimental results show that
learning from noisy labels can be effective for data-driven software and
security analytics.

7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
35
The categories of this paper are: mtrl-th