Write a Blog >>
MSR 2022
Mon 23 - Tue 24 May 2022
co-located with ICSE 2022
Thu 19 May 2022 21:07 - 21:14 at MSR Main room - odd hours - Session 13: Security & Quality Chair(s): Gias Uddin

Current machine-learning based software vulnerability detection methods are primarily conducted at the function-level. However, a key limitation of these methods is that they do not indicate the specific lines of code contributing to vulnerabilities. This limits the ability of developers to efficiently inspect and interpret the predictions from a learnt model, which is crucial for integrating machine-learning based tools into the software development workflow. Graph-based models have shown promising performance in function-level vulnerability detection, but their capability for statement-level vulnerability detection has not been extensively explored. While interpreting function-level predictions through explainable AI is one promising direction, we herein consider the statement-level software vulnerability detection task from a fully supervised learning perspective. We propose a novel deep learning framework, LineVD, which formulates statement-level vulnerability detection as a node classification task. LineVD leverages control and data dependencies between statements using graph neural networks, and a transformer-based model to encode the raw source code tokens. In particular, by addressing the conflicting outputs between function-level and statement-level information, LineVD significantly improve the prediction performance without vulnerability status for function code. We have conducted extensive experiments against a large-scale collection of real-world C/C++ vulnerabilities obtained from multiple real-world projects, and demonstrate an increase of 105% in F1-score over the current state-of-the-art.

Thu 19 May

Displayed time zone: Eastern Time (US & Canada) change

21:00 - 21:50
Session 13: Security & QualityTechnical Papers / Data and Tool Showcase Track / Registered Reports / Industry Track at MSR Main room - odd hours
Chair(s): Gias Uddin University of Calgary, Canada
21:00
7m
Talk
On the Use of Fine-grained Vulnerable Code Statements for Software Vulnerability Assessment Models
Technical Papers
Triet Le Huynh Minh The University of Adelaide, Muhammad Ali Babar University of Adelaide
Pre-print
21:07
7m
Talk
LineVD: Statement-level Vulnerability Detection using Graph Neural Networks
Technical Papers
David Hin The University of Adelaide, Andrey Kan The University of Adelaide, Huaming Chen The University of Adelaide, Muhammad Ali Babar University of Adelaide
21:14
7m
Talk
LineVul: A Transformer-based Line-Level Vulnerability Prediction
Technical Papers
Michael Fu Monash University, Chakkrit Tantithamthavorn Monash University
Pre-print
21:21
4m
Talk
ECench: An Energy Bug Benchmark of Ethereum Client Software
Data and Tool Showcase Track
Jinyoung Kim Sungkyunkwan University, Misoo Kim Sungkyunkwan University, Eunseok Lee Sungkyunkwan University
21:25
7m
Talk
Microsoft CloudMine: Data Mining for the Executive Order on Improving the Nation’s Cybersecurity
Industry Track
Kim Herzig Tools for Software Engineers, Microsoft, Luke Gostling Microsoft Corporation, Maximilian Grothusmann Microsoft Corporation, Nora Huang Microsoft Corporation, Sascha Just Microsoft, Alan Klimowski Microsoft Corporation, Yashasvini Ramkumar Microsoft Corporation, Myles McLeroy Microsoft Corporation, Kıvanç Muşlu Microsoft, Hitesh Sajnani Microsoft , Varsha Vadaga Microsoft Corporation
21:32
4m
Talk
Evaluating few shot and Contrastive learning Methods for Code Clone Detection
Registered Reports
Mohamad Khajezade University of British Columbia, Fatemeh Hendijani Fard University of British Columbia, Mohamed S Shehata University of British Columbia
Pre-print
21:36
14m
Live Q&A
Discussions and Q&A
Technical Papers


Information for Participants
Thu 19 May 2022 21:00 - 21:50 at MSR Main room - odd hours - Session 13: Security & Quality Chair(s): Gias Uddin
Info for room MSR Main room - odd hours:

Click here to go to the room on Midspace