Recruiting

Research Overview

The research topic of ARISE is on, as its name indicates, finding better ways for software engineers to develop software artifacts by invesigtating scientific methodologies and automated tools. We see that the security and safety of our society is getting more severly threatened by poor quality software products and the inabilities of engineers to manage software qualities. To address these challenges, we study the phenomena of software developments and the principles of computing to understand when, where, why and how unreliable, insecure, or unsafe software is resulted. We investigate techniques, methodologies, and pedagogies to improve the abilities of software developers in engineering software artifacts for constructing, analyzing, testing, and debugging programs and data.

The research programmes of ARISE aim to developing new techniques of test generation and automated debugging and associating them effectively to the software development processes. The recent research projects of ARISE includes the followings:

• Automating Code Edit for Resolving MISRA Violations (w/ SuresoftTech Inc.)

• BugOss: A Regression Bug Benchmark for Evaluating Regression Fuzzing Techniques

• DoTeLink: Inferring Fine-grained Traceability between Javadoc sentences and JUnit test code regions 

• Change-aware Greybox Fuzzing for Continuous Unit Test Generation (w/ SAP Labs Korea)

• MuTrain: Project-specific Mutant Reduction using Machine Learning

• LMMU: Neural Language Model-based Mutation Operator for Plausible Source Code Mutation

• DeMiner: mutation-guided symbolic execution for testing C programs,

• CRESTIVE: extending Concolic testing techniques for better scalability and usability,

• MUSEUM+: improved mutation-based debugging for omission faults,

• FindTestBugs: static analysis bug detector for flaky test bugs in JUnit code

And the list of the on-going research projects is as follows (at Oct 2023):

• Development of automatic software error repair technology that combines code analysis and error mining, IITP, 2021-2024

• Log-based Fuzzing for testing IoT device software, Center for Software Disaster Research, Excellent Research Center (ERC), NRF, 2021-2028 

Education Plan

We hope to foster motivated students who are interested in software engineering, programming language, security, and computer systems to grow them into professionals in software engineering. The students enrolled in ARISE will have chance to take relevant courses and participate in government-funded/industrial research projects to equip essential aspects of software engineering and software engineering research, including:

• Fundamentals of computation logics for reasoning program behaviors

• In-depth understanding of software testing and analysis techniques

• Skills for engineering source code and software artifacts (e.g., source code, binary code)

• Ability to apply machine learning techniques to analyze software-related data

• Experiences in developing and testing system programs (e.g., embedded software)

The current and former members of ARISE have been recognized by many awards for their outstanding research works, for recent examples:

• Jeewoong Kim, 2nd Prize at BK21 Outstanding Research Award, Sep 2023

• Hanyoung Yoo, BK21 Master's Thesis Award, Handong Global University, Feb 2022

• Hansol Choe, Outstanding Master's Thesis Award, Handong Global University, Feb 2021

• Juyoung Jeon, BK21 Master's Thesis Award, Handong Global University, Feb 2021

• Hansol Choe, Best Short Paper Award, Korean Software Engineering Conference (KCSE), Feb 2020

• Juyoung Jeon, Best Paper Award (Soft ware Engineering), Korean Software Congress (KSC), Dec 2019

• Juyoung Jeon, First Rank (Winner), CodRep 2019: Machine Learning on Software Code Competition, Oct 2019

• Hansol Choe, Best Paper Award, Korean Computer Congress (KCC), Jun 2019

Supports

Full-time graduate students have opportunities to hold Research Assistant administrated by ARISE lab, and Teaching Assistant administrated by the school. Depending on their participation and achievement, a master’s degree program student will receive 1,300,000 KRW to 2,200,000 KRW monthly, and a Ph.D degree program student 1,600,000 KRW to 3,000,000 KRW monthly (not including the supports from scholarship if exists).

In addition, the school offers a tuition discount (up to 65%) for excellent newcomers. Furthermore, a graduate student of the ARISE lab can apply for various financial support programs of the Brain Korea 21 project held by the AI Research Center of Handong Global University (http://bk21ai.handong.edu), including industrial scholarship (depending on research achievement) and various research activity sponsorship.

Each student will be given an office space on campus, as well as full-fledged research equipment including high-end laptop, computing server, and cloud computer accesses Graduate students also have opportunities to live in on-campus dormitories.

Prospective Students (How to Contact)

You can find the recent publications at the lab website: http://arise.handong.edu. You can also find more on Professor Shin Hong at his webpage: http://hongshin.github.io.

If you are interested in applying to ARISE lab for your graduate study, please Professor Shin Hong via email (hongshin@handong.edu) to schedule an online meeting. Based on the meeting results, you may receive a recommendation letter to submit with an admission to the graduate school of Handong Global University.