ARISE Lab

Advancing Reliability, Safety & Security in Software Engineering

We study the principles of computing and the phenomena of software developments to understand when, where, why and how unreliable, insecure, or unsafe software is resulted and threatening in our society. We aim to resolve these problems by developing techniques, tools, methodologies and pedagogies that enhance the ability of developers in analyzing, testing, and debugging their software products.

News

16 Apr 2021 Recruiting New Grad Students (2021 Autom) [English]
2021년 후기 대학원 신입생 모집 [
Korean]

19 Feb 2021 Congrats Hansol and Juyoung on their graduation!

28 Nov 2020 Hansol and Juyoung defended their MS theses successfully

Shin Hong 홍신

Assistant Professor, CSEE in Handong Global University

Ph.D in Computer Science, KAIST 2015

hongshin@handong.edu, https://hongshin.github.io

313, Oseok Hall, Handong Global University

+82-54-260-1409

Jeewoong Kim 김지웅

Master's degree program (started in Sep 2018)

jeewoong@handong.edu

318, Oseok Hall, Handong Global University

Hanyoung Yoo 유한영

Master's degree program (started in Mar 2020)

hanyoungyoo@handong.edu

318, Oseok Hall, Handong Global University

Past Members

Juyoung Jeon (전주영)

  • Master's Degree, Mar 2019-Feb 2021

  • Thesis: Improving Mutation Based Fault Localization for Omission Faults (BK 21 Master's Thesis Award)

Hansol Choe (최한솔), now in Suresoft Technologies Inc.

  • Master's Degree, Mar 2018-Feb 2021

  • Thesis: Concolic Testing Search Strategies for Mitigating Path-space Local Search Problem (Master's Thesis Award)

Research Projects

Fuzz Testing for Effective Continuous Testing on Evolving Software, NRF, 2020-2022

Fuzzing for Improving Unit-level Testing, SAP Labs Korea, 2020, 2021

Intelligent Automation Techniques for Fullstack Software Debugging, Next-Generation Information Computing Development Program Funded by NRF, 2017-2020

Establishing Code Change Traceability Using Source Code Embedding (in direction of Prof. Shin Yoo at KAIST), Samsung Research, 2020

Design of Online Model Training and Prediction Environment for Reproducible Machine Learning Artifact Archiving (in collaboration with Prof. Charmgil Hong at Handong University), KISTI, 2020

Automated Method of Assessing Test Artifacts Quality (in direction of Prof. Shin Yoo at KAIST), Samsung Research, 2019

Developing Automated Software Test Generation Techniques Using Data-driven Analyses, Young Researcher Program Funded by NRF, 2017-2019

More ...