46 citations · 50 across the 4 of their papers we have counts for
6 papers
On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Models
Triet H. M. Le, M. Ali Babar
Many studies have developed Machine Learning (ML) approaches to detect Software Vulnerabilities (SVs) in functions and fine-grained code statements that cause such SVs. However, th…
Automated Security Assessment for the Internet of Things
Xuanyu Duan, Mengmeng Ge, Triet H. M. Le +4
Internet of Things (IoT) based applications face an increasing number of potential security risks, which need to be systematically assessed and addressed. Expert-based manual asses…
DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning
Triet H. M. Le, David Hin, Roland Croft +1
It is increasingly suggested to identify Software Vulnerabilities (SVs) in code commits to give early warnings about potential security risks. However, there is a lack of effort to…
Automated Software Vulnerability Assessment with Concept Drift
Triet H. M. Le, Bushra Sabir, M. Ali Babar
Software Engineering researchers are increasingly using Natural Language Processing (NLP) techniques to automate Software Vulnerabilities (SVs) assessment using the descriptions in…
PUMiner: Mining Security Posts from Developer Question and Answer Websites with PU Learning
Triet H. M. Le, David Hin, Roland Croft +1
Security is an increasing concern in software development. Developer Question and Answer (Q&A) websites provide a large amount of security discussion. Existing studies have used hu…
Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges
Triet H. M. Le, Hao Chen, M. Ali Babar
Deep Learning (DL) techniques for Natural Language Processing have been evolving remarkably fast. Recently, the DL advances in language modeling, machine translation and paragraph…