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Fang-Hsiang Su
Fang-Hsiang Su
Computer Science, Columbia University
Verified email at cs.columbia.edu
Title
Cited by
Cited by
Year
Code relatives: detecting similarly behaving software
FH Su, J Bell, K Harvey, S Sethumadhavan, G Kaiser, T Jebara
Proceedings of the 2016 24th ACM SIGSOFT International Symposium on …, 2016
752016
Identifying functionally similar code in complex codebases
FH Su, J Bell, G Kaiser, S Sethumadhavan
2016 IEEE 24th International Conference on Program Comprehension (ICPC), 1-10, 2016
502016
Dynamic inference of likely metamorphic properties to support differential testing
FH Su, J Bell, C Murphy, G Kaiser
Proceedings of the 10th International Workshop on Automation of Software …, 2015
372015
Why do programs have heavy tails?
H Sasaki, FH Su, T Tanimoto, S Sethumadhavan
2017 IEEE International Symposium on Workload Characterization (IISWC), 135-145, 2017
92017
Challenges in behavioral code clone detection
FH Su, J Bell, G Kaiser
2016 IEEE 23rd International Conference on Software Analysis, Evolution, and …, 2016
82016
Obfuscation resilient search through executable classification
FH Su, J Bell, G Kaiser, B Ray
Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine …, 2018
52018
Service oriented platform design for collaborative engineering data analysis
JR Lee, SC Chang, FH Su, CM Fan
2007 International Symposium on Semiconductor Manufacturing, 1-4, 2007
52007
EXOS: Expansion on session for enhancing effectiveness of query auto-completion
FH Su, M Somaiya, S Mishra, R Mukherjee
2015 IEEE International Conference on Big Data (Big Data), 1154-1163, 2015
32015
Metamorphic runtime checking of applications without test oracles
C Murphy, J Bell, FH Su, G Kaiser
Technical Report CUCS-023-13, 2013
32013
Code relatives detection
FS Su, L Sethumadhavan, GE Kaiser, T Jebara
US Patent App. 15/549,785, 2018
22018
Code Relatives: Detecting Similar Software Behavior
F Su, K Harvey, S Sethumadhavan, G Kaiser, T Jebara
Department of Computer Science, Columbia University, 2015
22015
Heavy tails in program structure
H Sasaki, FH Su, T Tanimoto, S Sethumadhavan
IEEE Computer Architecture Letters 16 (1), 34-37, 2017
12017
A novel ontology-based knowledge engineering approach for yield symptom identification in semiconductor manufacturing
FH Su, SC Chang, CM Fan, YJ Tsai, J Jheng, CP Kao, CY Lu
2009 IEEE International Conference on Automation Science and Engineering …, 2009
12009
Uncovering features in kindred programs
FH Su
2017 IEEE/ACM 39th International Conference on Software Engineering …, 2017
2017
Code relatives detection
F Su, L Sethumadhavan, GE Kaiser, T Jebara
WO Patent App. WO2016130542A1, 2016
2016
Enhanced search query suggestions
MH Somaiya, R Mukherjee, S Mishra, FH Su
US Patent App. 14/818,034, 2016
2016
Ontology model to accelerate engineering analysis in manufacturing
YJ Tsai, CM Fan, SC Chang, HC Cheng, FH Su, WC Chen, CP Kao
US Patent 8,510,254, 2013
2013
Knowledge engineering of analysis tool application processes for yield symptom identification
FH Su, SC Chang, YJ Tsai, CY Lu, CM Fan
2008 International Symposium on Semiconductor Manufacturing (ISSM), 261-262, 2008
2008
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