Personal Information
Organización/Lugar de trabajo
Hong Kong, Hong Kong S.A.R. Hong Kong
Ocupación
Associate Prof.
Sector
Education
Sitio web
www.cse.ust.hk/~hunkim
Acerca de
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
Etiquetas
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
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Personal Information
Organización/Lugar de trabajo
Hong Kong, Hong Kong S.A.R. Hong Kong
Ocupación
Associate Prof.
Sector
Education
Sitio web
www.cse.ust.hk/~hunkim
Acerca de
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
Etiquetas
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
Ver más