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Jooyong Yi

Ulsan National Institute of Science and Technology · 情報科学

研究室紹介

Professor Jooyong Yi's research lab specializes in automated program repair (APR), focusing on developing intelligent, semantics-based techniques that generate high-quality, human-readable patches while preserving program structure. The lab emphasizes simplicity and correctness in repairs, aiming to bridge the gap between automated fixes and developer acceptance. Their work also explores the integration of APR with educational tools, such as intelligent tutoring systems, to support programming education. Additionally, the lab contributes to benchmarking and evaluating repair tools across diverse fault types to improve the reliability and practicality of automated debugging solutions.

automated program repairprogram synthesissoftware debuggingsoftware engineeringprogramming education

Research Overview

Papers
44
Total Citations
1,343
Papers (5y)
16
Primary Field
情報科学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
16total
2020
2022
2023
2024
2025
Citations per year (5y)
46total
20202022202320242025

Selected Papers

15
1
Article|509 citations·2016
Angelix
Sergey Mechtaev, Jooyong Yi, Abhik Roychoudhury

Since debugging is a time-consuming activity, automated program repair tools such as GenProg have garnered interest. A recent study revealed that the majority of GenProg repairs avoid bugs simply by deleting functionality. We found that SPR, a state-of-the-art repair tool proposed in 2015, still deletes functionality in their many "plausible" repairs. Unlike generate-and-validate systems such as GenProg and SPR, semantic analysis based repair techniques synthesize a repair based on semantic info

SoftwareComputer Science
2
Article|177 citations·2015
DirectFix: Looking for Simple Program Repairs
Sergey Mechtaev, Jooyong Yi, Abhik Roychoudhury
2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

Recent advances in program repair techniques have raised the possibility of patching bugs automatically. For an automatically generated patch to be accepted by developers, it should not only resolve the bug but also satisfy certain human-related factors including readability and comprehensibility. In this paper, we focus on the simplicity of patches (the size of changes). We present a novel semantics-based repair method that generates the simplest patch such that the program structure of the bug

SoftwareComputer Science
3
Article|169 citations·2015
DirectFix: looking for simple program repairs
Sergey Mechtaev, Jooyong Yi, Abhik Roychoudhury
UCL Discovery (University College London)OA

Recent advances in program repair techniques have raised the possibility of patching bugs automatically. For an automatically generated patch to be accepted by developers, it should not only resolve the bug but also satisfy certain humanrelated factors including readability and comprehensibility. In this paper, we focus on the simplicity of patches (the size of changes). We present a novel semantics-based repair method that generates the simplest patch such that the program structure of the bugg

SoftwareComputer Science
4
Article|127 citations·2017
Codeflaws: a programming competition benchmark for evaluating automated program repair tools
Shin Hwei Tan, Jooyong Yi, Yulis, Sergey Mechtaev, Abhik Roychoudhury

Several automated program repair techniques have been proposed to reduce the time and effort spent in bug-fixing. While these repair tools are designed to be generic such that they could address many software faults, different repair tools may fix certain types of faults more effectively than other tools. Therefore, it is important to compare more objectively the effectiveness of different repair tools on various fault types. However, existing benchmarks on automated program repairs do not allow

SoftwareComputer Science
5
Article|111 citations·2017
A feasibility study of using automated program repair for introductory programming assignments
Jooyong Yi, Umair Z. Ahmed, Amey Karkare, Shin Hwei Tan, Abhik Roychoudhury

Despite the fact an intelligent tutoring system for programming (ITSP) education has long attracted interest, its widespread use has been hindered by the difficulty of generating personalized feedback automatically. Meanwhile, automated program repair (APR) is an emerging new technology that automatically fixes software bugs, and it has been shown that APR can fix the bugs of large real-world software. In this paper, we study the feasibility of marrying intelligent programming tutoring and APR.

SoftwareComputer Science
6
Article|44 citations·2017
What do software engineers care about? gaps between research and practice
Vladimir Ivanov, Alan J. Rogers, Giancarlo Succi, Jooyong Yi, V Zorin

It is a cliche to say that there is a gap between research and practice. As the interest and importance in the practical impact of research has been growing, the gap between research and practice is expected to be narrowing. However, our study reveals that there still seems to be a wide gap. We survey so ware engineers about what they care about when developing so ware. We then compare our survey results with the research topics of the papers published in ICSE/FSE recently. We found the followin

Information SystemsComputer Science
7
Article|35 citations·2017
A correlation study between automated program repair and test-suite metrics
Jooyong Yi, Shin Hwei Tan, Sergey Mechtaev, Marcel Böhme, Abhik Roychoudhury
SJR Q1Empirical Software Engineering
SoftwareComputer Science
8
Article|20 citations·2018
Design and validation of precooked developer dashboards
Vladimir Ivanov, Vladislav Pischulin, Alan J. Rogers, Giancarlo Succi, Jooyong Yi, V Zorin

Despite increasing popularity of developer dashboards, the effectiveness of dashboards is still in question. In order to design a dashboard that is effective and useful for developers, it is important to know (a) what information developers need to see in a dashboard, and (b) how developers want to use a dashboard with that necessary information. To answer these questions, we conducted two series of face-to-face individual interviews with developers. In the first step we analyzed answers, build

Information SystemsComputer Science
9
Article|15 citations·2022
Speeding up constraint-based program repair using a search-based technique
Jooyong Yi, Elkhan Ismayilzada
SJR Q1Information and Software TechnologyOA
SoftwareComputer Science
10
Article|14 citations·2018
A correlation study between automated program repair and test-suite metrics
Jooyong Yi, Shin Hwei Tan, Sergey Mechtaev, Marcel Böhme, Abhik Roychoudhury

Automated program repair has attracted attention due to its potential to reduce debugging cost. Prior works show the feasibility of automated repair, and the research focus is gradually shifting towards the quality of generated patches. One promising direction is to control the quality of generated patches by controlling the quality of test-suites used. In this paper, 1we investigate the question: "Can traditional test-suite metrics used in software testing be used for automated program repair?"

SoftwareComputer Science
11
Article|14 citations·2013
Expressing and checking intended changes via software change contracts
Jooyong Yi, Dawei Qi, Shin Hwei Tan, Abhik Roychoudhury

Software errors often originate from incorrect changes, including incorrect program fixes, incorrect feature updates and so on. Capturing the intended program behavior explicitly via contracts is thus an attractive proposition. In our recent work, we had espoused the notion of "change contracts" to express the intended program behavior changes across program versions. Change contracts differ from program contracts in that they do not require the programmer to describe the intended behavior of pr

Information SystemsComputer Science
12
Article|13 citations·2018
Understanding the impact of pair programming on the minds of developers
Sara Busechian, Vladimir Ivanov, Alan J. Rogers, Ilyas Sirazitdinov, Giancarlo Succi, Alexander Tormasov, Jooyong Yi

Software is mostly, if not entirely, a knowledge artifact. Software best practices are often thought to work because they induce more productive behaviour in software developers. In this paper we deployed a new generation tool, portable multichannel EEG, to obtain direct physical insight into the mental processes of working software developers engaged in their standard activities. We have demonstrated the feasibility of this approach and obtained a glimpse of its potential power to distinguish p

Cognitive NeuroscienceNeuroscience
13
Article|10 citations·2023
BUGSC++: A Highly Usable Real World Defect Benchmark for C/C++
Gabin An, Minhyuk Kwon, Kyunghwa Choi, Jooyong Yi, Shin Yoo

As software systems grow larger and more complex, debugging takes up an increasingly significant portion of developers' time and efforts during software maintenance. To aid software engineers in debugging, many automated debugging and repair techniques have been proposed. Both the development and evaluation of these automated techniques depend on benchmarks of bugs. While many different defect benchmarks have been developed, only a few benchmarks are widely used due to the origin of the collecte

SoftwareComputer Science
14
Article|9 citations·2018
Precooked developer dashboards
Vladimir Ivanov, Alan J. Rogers, Giancarlo Succi, Jooyong Yi, Vasiii Zorin

Designing an effective and useful dashboard is expensive and it would be important to determine if it is possible to elaborate a "generic" useful and effective dashboard, usable in a variety of circumstances. To determine if it is possible to develop such dashboard and, if so, its structure we interviewed 67 software engineers from 44 different companies. Their answers made us confident in the possibility of building such dashboard.

Information SystemsComputer Science
15
Article|9 citations·2018
A new architecture and implementation strategy for non-invasive software measurement systems
Anton Bykov, Vladimir Ivanov, Alan J. Rogers, Alexandr Shunevich, Alberto Sillitti, Giancarlo Succi, Alexander Tormasov, Jooyong Yi, Albert Zabirov, Denis Zaplatnikov

Despite that non-invasive software measurement tools have proven their usefulness in software production, their adoption in software industry is still limited. Reasons for the limited distributions have been studied and analysed recently. In this paper, we propose a new architecture for non-invasive software measurement systems that address the problems of the existing systems. The outcome of our early experimentation is quite promising and gives us the desired additional confidence on its succe

Information SystemsComputer Science

Research Areas

SoftwareInformation SystemsArtificial IntelligenceManagement Science and Operations ResearchCognitive NeurosciencePlant Science

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