SlideShare une entreprise Scribd logo
  • Mettre en ligne
  • Accueil
  • Explorer
  • S’identifier
  • S’inscrire
SlideShare une entreprise Scribd logo
  • Accueil
  • Explorer
  • Mettre en ligne
  • S’identifier
  • S’inscrire

Nous avons mis à jour notre politique de confidentialité. Cliquez ici pour consulter les détails. Cliquez ici pour consulter les détails.

×
×
×
×
×
×
Sung Kim

Sung Kim

873 Abonné
45 SlideShares 1 Clipboard 873 Abonné 207 Suivis
  • Débloquer l’utilisateur Bloquer l’utilisateur
45 SlideShares 1 Clipboard 873 Abonné 207 Suivis

Personal Information
Entreprise/Lieu de travail
Hong Kong, Hong Kong S.A.R. Hong Kong
Profession
Associate Prof.
Secteur d’activité
Education
Site Web
www.cse.ust.hk/~hunkim
À propos
Sung is an associate professor at the Hong Kong University of Science and Technology. He was a post-doc at the Program Analysis Group at MIT. He received his Ph.D. (thesis: Adaptive Bug Prediction By Analyzing Software History) in the Computer Science Department at the University of California, Santa Cruz. He has worked for Nara Vision Co. Ltd which is one of the leading Internet software companies in Korea for six years as a CTO. His research area is Software Engineering, focusing on software evolution, repository data mining, development social network mining, program analysis, and empirical studies. His chief research interest is programmer productivity, in particular, identifying faults
Mots-clés
defect prediction deeplearning software testing fse hkust crash software engineering developers icse2011 deep api tensorflow machinelearning tensorboard software evolution debugging stackoverflow machine learning commit msr bug fault localization sna survey changes software development process tao intelligence code search engine instant code search tossing bug triage kenyon dsn2011
Tout plus
Présentations (45)
Tout voir
Predicting Faults from Cached History
il y a 15 ans • 1754 Vues
Which Warnings Should I Fix First?
il y a 15 ans • 1399 Vues
Dissertation Defense
il y a 15 ans • 16910 Vues
Memories of Bug Fixes
il y a 15 ans • 1442 Vues
Signature Change Analysis
il y a 15 ans • 1240 Vues
Static and Adaptive Bug Fix Patterns
il y a 15 ans • 782 Vues
MeCC: Memory Comparison based Clone Detector
il y a 11 ans • 1726 Vues
Dealing with Noise in Defect Prediction
il y a 11 ans • 1898 Vues
"Crash Graphs: An Aggregated View of Multiple Crashes to Improve Crash Triage" by Sunghun Kim, Thomas Zimmermann and Nachiappan Nagappan.
il y a 11 ans • 2030 Vues
Micro Interaction Metrics for Defect Prediction (ESEC/FSE 2011)
il y a 10 ans • 1701 Vues
ReLink: Recovering Links between Bugs and Changes (ESEC/FSE 2011)
il y a 10 ans • 1699 Vues
OCAT: Object Capture based Automated Testing (ISSTA 2010)
il y a 10 ans • 1434 Vues
Kenyon: A Software Stratigraphy Platform (ESEC/FSE 2005)
il y a 10 ans • 1754 Vues
CosTriage: A Cost-Aware Algorithm for Bug Reporting Systems (AAAI 2011)
il y a 10 ans • 2030 Vues
ReCrash: Making crashes reproducible by preserving object states (ECOOP 2008)
il y a 10 ans • 1715 Vues
Self-defending software: Automatically patching errors in deployed software (SOSP 2009)
il y a 10 ans • 1642 Vues
BugTriage with Bug Tossing Graphs (ESEC/FSE 2009)
il y a 10 ans • 2096 Vues
Software Development Meets the Wisdom of Crowds
il y a 10 ans • 1403 Vues
Puzzle-Based Automatic Testing: Bringing Humans Into the Loop by Solving Puzzles (ASE 2012)
il y a 10 ans • 1814 Vues
Predicting Recurring Crash Stacks (ASE 2012)
il y a 10 ans • 1612 Vues
Defect, defect, defect: PROMISE 2012 Keynote
il y a 10 ans • 4500 Vues
How Do Software Engineers Understand Code Changes? FSE 2012
il y a 10 ans • 1767 Vues
A Survey on Automatic Test Generation and Crash Reproduction
il y a 10 ans • 2046 Vues
The Anatomy of Developer Social Networks
il y a 10 ans • 835 Vues
Automatic patch generation learned from human written patches
il y a 9 ans • 9178 Vues
Transfer defect learning
il y a 9 ans • 3120 Vues
STAR: Stack Trace based Automatic Crash Reproduction
il y a 9 ans • 6956 Vues
Personalized Defect Prediction
il y a 9 ans • 3693 Vues
MSR2014 opening
il y a 8 ans • 16858 Vues
Survey on Software Defect Prediction
il y a 8 ans • 13967 Vues
J’aime (81)
Tout voir
TinyBERT
Hoon Heo • il y a 3 ans
작고 빠른 딥러닝 그리고 Edge computing
StellaSeoYeonYang • il y a 3 ans
NLP Deep Learning with Tensorflow
seungwoo kim • il y a 5 ans
Tensorflow for Deep Learning(SK Planet)
Tae Young Lee • il y a 5 ans
[224]nsml 상상하는 모든 것이 이루어지는 클라우드 머신러닝 플랫폼
NAVER D2 • il y a 5 ans
Linear algebra
Sungbin Lim • il y a 5 ans
Generative adversarial networks
남주 김 • il y a 6 ans
CNN 초보자가 만드는 초보자 가이드 (VGG 약간 포함)
Lee Seungeun • il y a 5 ans
강화 학습 기초 Reinforcement Learning an introduction
Taehoon Kim • il y a 6 ans
Paper Reading : Enriching word vectors with subword information(2016)
정훈 서 • il y a 6 ans
One-Shot Learning
Jisung Kim • il y a 6 ans
지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016
Taehoon Kim • il y a 6 ans
Introduction to Amazon Web Services
Amazon Web Services • il y a 11 ans
부동산 텔레그램 봇
HoChul Shin • il y a 6 ans
Explanation on Tensorflow example -Deep mnist for expert
홍배 김 • il y a 6 ans
NDC 2016 김정주 - 기계학습을 활용한 게임어뷰징 검출
정주 김 • il y a 6 ans
Caffe framework tutorial2
Park Chunduck • il y a 7 ans
기계학습 / 딥러닝이란 무엇인가
Yongha Kim • il y a 6 ans
Google TensorFlow Tutorial
台灣資料科學年會 • il y a 7 ans
Synchronise your data between MySQL and MongoDB
Giuseppe Maxia • il y a 9 ans
[123] quality without qa
NAVER D2 • il y a 7 ans
깃헙으로 코드리뷰 하기
Ohgyun Ahn • il y a 10 ans
코드 리뷰 시스템 소개
Young-Ho Cha • il y a 7 ans
Introduce Docker
Yongbok Kim • il y a 7 ans
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Lean Analytics • il y a 8 ans
공짜 경제에서 어떻게 돈을 버는가?(How to Make Money in Free Economy)
Sangkyu Rho • il y a 7 ans
[1주차] 알파 유저를 위한 AWS 스터디
Amazon Web Services Korea • il y a 7 ans
AWS Summit Seoul 2015 - 모바일 및 IoT 환경을 위한 AWS 클라우드 플랫폼의 진화 (윤석찬, Markku Lepisto)
Amazon Web Services Korea • il y a 7 ans
Continous UI testing with Espresso and Jenkins
Sylwester Madej • il y a 7 ans
Evaluating the Usefulness of IR-Based Fault LocalizationTechniques
Alex Orso • il y a 7 ans
Open Source 그리고 git과 github, code review
Minsuk Lee • il y a 7 ans
AWS 클라우드 기반 확장성 높은 천만 사용자 웹 서비스 만들기 - 윤석찬
Amazon Web Services Korea • il y a 7 ans
스타트업에서 기술책임자로 살아가기
Hyun-woo Park • il y a 8 ans
Welcome to ICSE NIER’15 (new ideas and emerging results).
CS, NcState • il y a 7 ans
[IoT] MAKE with Open H/W + Node.JS - 2nd
Park Jonggun • il y a 7 ans
[IoT] MAKE with Open H/W + Node.JS - 1st
Park Jonggun • il y a 7 ans
Requirements Engineering
CS, NcState • il y a 7 ans
Node.js 기본
Han Jung Hyun • il y a 9 ans
Towards Mining Software Repositories Research that Matters
Tao Xie • il y a 8 ans
Spark overview 이상훈(SK C&C)_스파크 사용자 모임_20141106
SangHoon Lee • il y a 8 ans
Known Unknowns: Testing in the Presence of Uncertainty (talk at ACM SIGSOFT FSE 2014 Visions & Challenges Track)
David Rosenblum • il y a 8 ans
한국 웹 초창기 비하인드 스토리
removed_b20733aef4c19a1ab5010e5f64114bd0 • il y a 8 ans
How Google Works
Eric Schmidt • il y a 8 ans
How Google Works / 구글은 어떻게 일하는가 (Korean / 한국어 버전)
Mika Eunjin Kang • il y a 8 ans
소프트웨어개발자는누구인가?
Minsuk Lee • il y a 8 ans
[PreSchool-1] 프로그래밍 '개념' 맛보기
Young-Ho Cho • il y a 8 ans
Career Management (invited talk at ICSE 2014 NFRS)
David Rosenblum • il y a 8 ans
The Art and Science of Analyzing Software Data
CS, NcState • il y a 8 ans
논문 잘 읽는 법
Suhkyung Kim • il y a 9 ans
Replication and Benchmarking in Software Analytics
University of Zurich • il y a 9 ans
Jubula tutorial slides
bredex • il y a 11 ans
Jubula tutorial EclipseCon North America 2012
bredex • il y a 10 ans
Warning: don't do CS
CS, NcState • il y a 9 ans
Franhouder july2013
CS, NcState • il y a 9 ans
The 3 Secrets of Highly Successful Graduates
Reid Hoffman • il y a 9 ans
What I Carry: 10 Tools for Success
Jonathon Colman • il y a 9 ans
Daum’s Business Analytics Use-cases based on Bigdata technology (2012)
Channy Yun • il y a 9 ans
What Would Steve Do? 10 Lessons from the World's Most Captivating Presenters
HubSpot • il y a 9 ans
svn 능력자를 위한 git 개념 가이드
Insub Lee • il y a 9 ans
소프트웨어 아키텍처
영기 김 • il y a 9 ans
The Zen of Scrum
Jurgen Appelo • il y a 13 ans
스크럼, 이걸 왜 하나요
Insub Lee • il y a 10 ans
Automated Debugging: Are We There Yet?
Alex Orso • il y a 9 ans
KAIST 후배들을 위한 유학에 관한 이야기
Sang-il Oum • il y a 11 ans
[홍순성]보다 쉽게 찾는 나만의 정리법
@hongss • il y a 10 ans
Whither Software Engineering Research? (keynote talk at APSEC 2012)
David Rosenblum • il y a 10 ans
Analytics for smarter software development
Thomas Zimmermann • il y a 10 ans
Cra mentoring 2012 students
David Notkin • il y a 10 ans
SSBSE 2012 Keynote
Massimiliano Di Penta • il y a 10 ans
Machine Learning and Data Mining: 12 Classification Rules
Pier Luca Lanzi • il y a 15 ans
ICSE 2011 Research Paper on Refactorings and Bug Fixes
miryung • il y a 11 ans
How to prototype and influence people
azaraskin • il y a 12 ans
Debugging Debugging
CISPA Helmholtz Center for Information Security • il y a 13 ans
Mining Software Archives to Support Software Development
Thomas Zimmermann • il y a 15 ans
Of Code and Change: Beautiful Software
Michele Lanza • il y a 14 ans
My Top 10 slides on presentations
Alexei Kapterev • il y a 14 ans
Death by PowerPoint
Alexei Kapterev • il y a 15 ans
Brain Rules for Presenters
garr • il y a 14 ans
How Developer Communication Frequency Relates to Bug Introducing Changes
Rahul Premraj • il y a 13 ans
Seminar on Software Testing
Beat Fluri • il y a 13 ans
Got Myth? Myths in Software Engineering
Thomas Zimmermann • il y a 15 ans
  • Activité
  • À propos

Présentations (45)
Tout voir
Predicting Faults from Cached History
il y a 15 ans • 1754 Vues
Which Warnings Should I Fix First?
il y a 15 ans • 1399 Vues
Dissertation Defense
il y a 15 ans • 16910 Vues
Memories of Bug Fixes
il y a 15 ans • 1442 Vues
Signature Change Analysis
il y a 15 ans • 1240 Vues
Static and Adaptive Bug Fix Patterns
il y a 15 ans • 782 Vues
MeCC: Memory Comparison based Clone Detector
il y a 11 ans • 1726 Vues
Dealing with Noise in Defect Prediction
il y a 11 ans • 1898 Vues
"Crash Graphs: An Aggregated View of Multiple Crashes to Improve Crash Triage" by Sunghun Kim, Thomas Zimmermann and Nachiappan Nagappan.
il y a 11 ans • 2030 Vues
Micro Interaction Metrics for Defect Prediction (ESEC/FSE 2011)
il y a 10 ans • 1701 Vues
ReLink: Recovering Links between Bugs and Changes (ESEC/FSE 2011)
il y a 10 ans • 1699 Vues
OCAT: Object Capture based Automated Testing (ISSTA 2010)
il y a 10 ans • 1434 Vues
Kenyon: A Software Stratigraphy Platform (ESEC/FSE 2005)
il y a 10 ans • 1754 Vues
CosTriage: A Cost-Aware Algorithm for Bug Reporting Systems (AAAI 2011)
il y a 10 ans • 2030 Vues
ReCrash: Making crashes reproducible by preserving object states (ECOOP 2008)
il y a 10 ans • 1715 Vues
Self-defending software: Automatically patching errors in deployed software (SOSP 2009)
il y a 10 ans • 1642 Vues
BugTriage with Bug Tossing Graphs (ESEC/FSE 2009)
il y a 10 ans • 2096 Vues
Software Development Meets the Wisdom of Crowds
il y a 10 ans • 1403 Vues
Puzzle-Based Automatic Testing: Bringing Humans Into the Loop by Solving Puzzles (ASE 2012)
il y a 10 ans • 1814 Vues
Predicting Recurring Crash Stacks (ASE 2012)
il y a 10 ans • 1612 Vues
Defect, defect, defect: PROMISE 2012 Keynote
il y a 10 ans • 4500 Vues
How Do Software Engineers Understand Code Changes? FSE 2012
il y a 10 ans • 1767 Vues
A Survey on Automatic Test Generation and Crash Reproduction
il y a 10 ans • 2046 Vues
The Anatomy of Developer Social Networks
il y a 10 ans • 835 Vues
Automatic patch generation learned from human written patches
il y a 9 ans • 9178 Vues
Transfer defect learning
il y a 9 ans • 3120 Vues
STAR: Stack Trace based Automatic Crash Reproduction
il y a 9 ans • 6956 Vues
Personalized Defect Prediction
il y a 9 ans • 3693 Vues
MSR2014 opening
il y a 8 ans • 16858 Vues
Survey on Software Defect Prediction
il y a 8 ans • 13967 Vues
J’aime (81)
Tout voir
TinyBERT
Hoon Heo • il y a 3 ans
작고 빠른 딥러닝 그리고 Edge computing
StellaSeoYeonYang • il y a 3 ans
NLP Deep Learning with Tensorflow
seungwoo kim • il y a 5 ans
Tensorflow for Deep Learning(SK Planet)
Tae Young Lee • il y a 5 ans
[224]nsml 상상하는 모든 것이 이루어지는 클라우드 머신러닝 플랫폼
NAVER D2 • il y a 5 ans
Linear algebra
Sungbin Lim • il y a 5 ans
Generative adversarial networks
남주 김 • il y a 6 ans
CNN 초보자가 만드는 초보자 가이드 (VGG 약간 포함)
Lee Seungeun • il y a 5 ans
강화 학습 기초 Reinforcement Learning an introduction
Taehoon Kim • il y a 6 ans
Paper Reading : Enriching word vectors with subword information(2016)
정훈 서 • il y a 6 ans
One-Shot Learning
Jisung Kim • il y a 6 ans
지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016
Taehoon Kim • il y a 6 ans
Introduction to Amazon Web Services
Amazon Web Services • il y a 11 ans
부동산 텔레그램 봇
HoChul Shin • il y a 6 ans
Explanation on Tensorflow example -Deep mnist for expert
홍배 김 • il y a 6 ans
NDC 2016 김정주 - 기계학습을 활용한 게임어뷰징 검출
정주 김 • il y a 6 ans
Caffe framework tutorial2
Park Chunduck • il y a 7 ans
기계학습 / 딥러닝이란 무엇인가
Yongha Kim • il y a 6 ans
Google TensorFlow Tutorial
台灣資料科學年會 • il y a 7 ans
Synchronise your data between MySQL and MongoDB
Giuseppe Maxia • il y a 9 ans
[123] quality without qa
NAVER D2 • il y a 7 ans
깃헙으로 코드리뷰 하기
Ohgyun Ahn • il y a 10 ans
코드 리뷰 시스템 소개
Young-Ho Cha • il y a 7 ans
Introduce Docker
Yongbok Kim • il y a 7 ans
Slides for the day-long Lean Analytics workshop at the 2014 Lean Startup conference
Lean Analytics • il y a 8 ans
공짜 경제에서 어떻게 돈을 버는가?(How to Make Money in Free Economy)
Sangkyu Rho • il y a 7 ans
[1주차] 알파 유저를 위한 AWS 스터디
Amazon Web Services Korea • il y a 7 ans
AWS Summit Seoul 2015 - 모바일 및 IoT 환경을 위한 AWS 클라우드 플랫폼의 진화 (윤석찬, Markku Lepisto)
Amazon Web Services Korea • il y a 7 ans
Continous UI testing with Espresso and Jenkins
Sylwester Madej • il y a 7 ans
Evaluating the Usefulness of IR-Based Fault LocalizationTechniques
Alex Orso • il y a 7 ans
Open Source 그리고 git과 github, code review
Minsuk Lee • il y a 7 ans
AWS 클라우드 기반 확장성 높은 천만 사용자 웹 서비스 만들기 - 윤석찬
Amazon Web Services Korea • il y a 7 ans
스타트업에서 기술책임자로 살아가기
Hyun-woo Park • il y a 8 ans
Welcome to ICSE NIER’15 (new ideas and emerging results).
CS, NcState • il y a 7 ans
[IoT] MAKE with Open H/W + Node.JS - 2nd
Park Jonggun • il y a 7 ans
[IoT] MAKE with Open H/W + Node.JS - 1st
Park Jonggun • il y a 7 ans
Requirements Engineering
CS, NcState • il y a 7 ans
Node.js 기본
Han Jung Hyun • il y a 9 ans
Towards Mining Software Repositories Research that Matters
Tao Xie • il y a 8 ans
Spark overview 이상훈(SK C&C)_스파크 사용자 모임_20141106
SangHoon Lee • il y a 8 ans
Known Unknowns: Testing in the Presence of Uncertainty (talk at ACM SIGSOFT FSE 2014 Visions & Challenges Track)
David Rosenblum • il y a 8 ans
한국 웹 초창기 비하인드 스토리
removed_b20733aef4c19a1ab5010e5f64114bd0 • il y a 8 ans
How Google Works
Eric Schmidt • il y a 8 ans
How Google Works / 구글은 어떻게 일하는가 (Korean / 한국어 버전)
Mika Eunjin Kang • il y a 8 ans
소프트웨어개발자는누구인가?
Minsuk Lee • il y a 8 ans
[PreSchool-1] 프로그래밍 '개념' 맛보기
Young-Ho Cho • il y a 8 ans
Career Management (invited talk at ICSE 2014 NFRS)
David Rosenblum • il y a 8 ans
The Art and Science of Analyzing Software Data
CS, NcState • il y a 8 ans
논문 잘 읽는 법
Suhkyung Kim • il y a 9 ans
Replication and Benchmarking in Software Analytics
University of Zurich • il y a 9 ans
Jubula tutorial slides
bredex • il y a 11 ans
Jubula tutorial EclipseCon North America 2012
bredex • il y a 10 ans
Warning: don't do CS
CS, NcState • il y a 9 ans
Franhouder july2013
CS, NcState • il y a 9 ans
The 3 Secrets of Highly Successful Graduates
Reid Hoffman • il y a 9 ans
What I Carry: 10 Tools for Success
Jonathon Colman • il y a 9 ans
Daum’s Business Analytics Use-cases based on Bigdata technology (2012)
Channy Yun • il y a 9 ans
What Would Steve Do? 10 Lessons from the World's Most Captivating Presenters
HubSpot • il y a 9 ans
svn 능력자를 위한 git 개념 가이드
Insub Lee • il y a 9 ans
소프트웨어 아키텍처
영기 김 • il y a 9 ans
The Zen of Scrum
Jurgen Appelo • il y a 13 ans
스크럼, 이걸 왜 하나요
Insub Lee • il y a 10 ans
Automated Debugging: Are We There Yet?
Alex Orso • il y a 9 ans
KAIST 후배들을 위한 유학에 관한 이야기
Sang-il Oum • il y a 11 ans
[홍순성]보다 쉽게 찾는 나만의 정리법
@hongss • il y a 10 ans
Whither Software Engineering Research? (keynote talk at APSEC 2012)
David Rosenblum • il y a 10 ans
Analytics for smarter software development
Thomas Zimmermann • il y a 10 ans
Cra mentoring 2012 students
David Notkin • il y a 10 ans
SSBSE 2012 Keynote
Massimiliano Di Penta • il y a 10 ans
Machine Learning and Data Mining: 12 Classification Rules
Pier Luca Lanzi • il y a 15 ans
ICSE 2011 Research Paper on Refactorings and Bug Fixes
miryung • il y a 11 ans
How to prototype and influence people
azaraskin • il y a 12 ans
Debugging Debugging
CISPA Helmholtz Center for Information Security • il y a 13 ans
Mining Software Archives to Support Software Development
Thomas Zimmermann • il y a 15 ans
Of Code and Change: Beautiful Software
Michele Lanza • il y a 14 ans
My Top 10 slides on presentations
Alexei Kapterev • il y a 14 ans
Death by PowerPoint
Alexei Kapterev • il y a 15 ans
Brain Rules for Presenters
garr • il y a 14 ans
How Developer Communication Frequency Relates to Bug Introducing Changes
Rahul Premraj • il y a 13 ans
Seminar on Software Testing
Beat Fluri • il y a 13 ans
Got Myth? Myths in Software Engineering
Thomas Zimmermann • il y a 15 ans
Personal Information
Entreprise/Lieu de travail
Hong Kong, Hong Kong S.A.R. Hong Kong
Profession
Associate Prof.
Secteur d’activité
Education
Site Web
www.cse.ust.hk/~hunkim
À propos
Sung is an associate professor at the Hong Kong University of Science and Technology. He was a post-doc at the Program Analysis Group at MIT. He received his Ph.D. (thesis: Adaptive Bug Prediction By Analyzing Software History) in the Computer Science Department at the University of California, Santa Cruz. He has worked for Nara Vision Co. Ltd which is one of the leading Internet software companies in Korea for six years as a CTO. His research area is Software Engineering, focusing on software evolution, repository data mining, development social network mining, program analysis, and empirical studies. His chief research interest is programmer productivity, in particular, identifying faults
Mots-clés
defect prediction deeplearning software testing fse hkust crash software engineering developers icse2011 deep api tensorflow machinelearning tensorboard software evolution debugging stackoverflow machine learning commit msr bug fault localization sna survey changes software development process tao intelligence code search engine instant code search tossing bug triage kenyon dsn2011
Tout plus

Modal header

  • À propos
  • Assistance clientèle
  • Conditions générales
  • Confidentialité
  • Droits d’auteur
  • Préférences en matière de cookies
  • Ne pas vendre ou partager mes informations personnelles
Français
English
Español
Português
Langue courante: Français
Deutsch

© 2023 SlideShare from Scribd

Nous avons mis à jour notre politique de confidentialité.

Nous avons mis à jour notre politique de confidentialité pour nous conformer à l'évolution des réglementations mondiales en matière de confidentialité et pour vous informer de la manière dont nous utilisons vos données de façon limitée.

Vous pouvez consulter les détails ci-dessous. En cliquant sur Accepter, vous acceptez la politique de confidentialité mise à jour.

Merci!

Afficher la politique de confidentialité mise à jour
Nous avons rencontré un problème, veuillez réessayer.