Rui Shu 束 锐

I am recently a Ph.D. candidate in the RAISE Lab (Real-world Artifical Intelligence for Software Engineering) at North Carolina State University, under the supervision of Dr. Tim Menzies. My interest includes machine learning optimization. I am expected to graduate in 2020.

I achieved my master degree in Peking University in 2014 and obtained my bachelor degree in Beijing Jiaotong University in 2010.

Email  /  CV  /  Google Scholar  /  GitHub  / 


I am now interested in machine learning optimization. I was working in Docker security issues, including identifying security vulnerabilities in Docker images, and detecting security anomalies in Docker containers using machine learning techniques.


Efficient Security Bug Report Classification using Epsilon Dominance
Rui Shu, Jianfeng Chen, Laurie Williams, Tim Menzies
In Submission, 2019

In this paper, we propose to apply epsilon donimance to achieve faster and more efficient security bug reports classification.

effort estimation

Sequential Model Optimization for Software Process Control
Tianpei Xia, Jianfeng Chen, Rui Shu, Tim Menzies
Technical Reports, TR-2019-5, 2019

In this paper, we propose to apply hyperparameter optimization in effort estimation.


Better Security Bug Report Classification via Hyperparameter Optimization
Rui Shu, Tianpei Xia, Laurie Williams, Tim Menzies
In submission, 2019

In this paper, we propose to apply hyperparameter optimization and data balancing techniques to improve Peters' FARSEC prediction results. On the one hand, we leverage an optimizer called differential evolution (DE) algorithm to optimize learners' hyperparameters. On the other hand, we use the synthetic minority oversampling technique (SMOTE) and a tuned version SMOTUNED to address the imbalanced class problem in bug report dataset. Our experiment results shown that our proposed approaches can efficiently improve the baseline prediction results.


A Study of Security Vulnerabilities on Docker Hub
Rui Shu, Xiaohui Gu, William Enck
Proceedings of the Seventh ACM on Conference on Data and Application Security and Privacy (CODASPY), 2017
project page

In this paper, we study the state of security vulnerabilities in Docker Hub images. We create a scalable Docker image vulnerability analysis (DIVA) framework that automatically discovers, downloads, and analyzes both official and community images on Docker Hub. Using our framework, we have studied 356,218 images and made several findings.

This paper is also introduced in the morning paper and ACM's official Twitter.


A Study of Security Isolation Techniques
Rui Shu, Peipei Wang, Sigmund A Gorski III, Benjamin Andow, Adwait Nadkarni, Luke Deshotels, Jason Gionta, William Enck, Xiaohui Gu
ACM Computing Surveys (CSUR), 2016
project page

This article seeks to understand existing security isolation techniques by systematically classifying different approaches and analyzing their properties. We provide a hierarchical classification structure for grouping different security isolation techniques.

Teaching Assistant

Automated Software Engineering(CSC 591 & 791) - Fall 2019 (NCSU)

Introduction to Computing - Java (CSC 116) - Spring & Summer 2019 (NCSU)

Operating System Principles (CSC 501) - Fall 2018 (NCSU)

Computer Organization and Assembly Language (CSC 236) - Fall 2017 (NCSU)

Design and Analysis of Algorithms (CSC 505) - Spring 2015 (NCSU)

Discrete Mathematics for Computer Scientists (CSC 226) - Spring 2015 (NCSU)

Programming Concept - Java (CSC 216) - Fall 2014 (NCSU)

Introduction to Information Technology - Fall 2012 (PKU)

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