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Jinhan Kim
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Publications
- 2023
- [j11]Jinhan Kim, Gabin An, Robert Feldt, Shin Yoo:
Learning test-mutant relationship for accurate fault localisation. Inf. Softw. Technol. 162: 107272 (2023) - [j10]Jinhan Kim, Robert Feldt, Shin Yoo:
Evaluating Surprise Adequacy for Deep Learning System Testing. ACM Trans. Softw. Eng. Methodol. 32(2): 42:1-42:29 (2023) - [c29]Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella, Shin Yoo:
Repairing DNN Architecture: Are We There Yet? ICST 2023: 234-245 - [c28]Jinhan Kim, Jongchan Park, Shin Yoo:
The Inversive Relationship Between Bugs and Patches: An Empirical Study. ICSTW 2023: 314-323 - [i7]Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova, Paolo Tonella, Shin Yoo:
Repairing DNN Architecture: Are We There Yet? CoRR abs/2301.11568 (2023) - [i6]Jinhan Kim, Jongchan Park, Shin Yoo:
The Inversive Relationship Between Bugs and Patches: An Empirical Study. CoRR abs/2303.00303 (2023) - [i5]Jinhan Kim, Gabin An, Robert Feldt, Shin Yoo:
Learning Test-Mutant Relationship for Accurate Fault Localisation. CoRR abs/2306.02319 (2023) - 2022
- [j9]Jinhan Kim, Juyoung Jeon, Shin Hong, Shin Yoo:
Predictive Mutation Analysis via the Natural Language Channel in Source Code. ACM Trans. Softw. Eng. Methodol. 31(4): 73:1-73:27 (2022) - [c27]Juyeon Yoon, Seungjoon Chung, Kihyuck Shin, Jinhan Kim, Shin Hong, Shin Yoo:
Repairing Fragile GUI Test Cases Using Word and Layout Embedding. ICST 2022: 291-301 - 2021
- [c26]Jinhan Kim, Gabin An, Robert Feldt, Shin Yoo:
Ahead of Time Mutation Based Fault Localisation using Statistical Inference. ISSRE 2021: 253-263 - [i4]Jinhan Kim, Juyoung Jeon, Shin Hong, Shin Yoo:
Predictive Mutation Analysis via Natural Language Channel in Source Code. CoRR abs/2104.10865 (2021) - 2020
- [c25]Jinhan Kim, Valeriy V. Savchenko, Kihyuck Shin, Konstantin S. Sorokin, Hyunseok Jeon, Georgiy A. Pankratenko, Sergey Markov, Chul-Joo Kim:
Automatic abnormal log detection by analyzing log history for providing debugging insight. ICSE (SEIP) 2020: 71-80 - [c24]Jinhan Kim, Jeongil Ju, Robert Feldt, Shin Yoo:
Reducing DNN labelling cost using surprise adequacy: an industrial case study for autonomous driving. ESEC/SIGSOFT FSE 2020: 1466-1476 - [i3]Jinhan Kim, Jeongil Ju, Robert Feldt, Shin Yoo:
Reducing DNN Labelling Cost using Surprise Adequacy: An Industrial Case Study for Autonomous Driving. CoRR abs/2006.00894 (2020) - 2019
- [j8]Jinhan Kim, Shin Yoo:
Software review: DEAP (Distributed Evolutionary Algorithm in Python) library. Genet. Program. Evolvable Mach. 20(1): 139-142 (2019) - [c23]Jinhan Kim, Robert Feldt, Shin Yoo:
Guiding deep learning system testing using surprise adequacy. ICSE 2019: 1039-1049 - [i2]Jinhan Kim, Gabin An, Robert Feldt, Shin Yoo:
Amortising the Cost of Mutation Based Fault Localisation using Statistical Inference. CoRR abs/1902.09729 (2019) - 2018
- [c22]Gabin An, Jinhan Kim, Shin Yoo:
Comparing line and AST granularity level for program repair using PyGGI. GI@ICSE 2018: 19-26 - [c20]Jinhan Kim, Michael G. Epitropakis, Shin Yoo:
Learning Without Peeking: Secure Multi-party Computation Genetic Programming. SSBSE 2018: 246-261 - [i1]Jinhan Kim, Robert Feldt, Shin Yoo:
Guiding Deep Learning System Testing using Surprise Adequacy. CoRR abs/1808.08444 (2018) - 2017
- [c18]Jinhan Kim, Junhwi Kim, Shin Yoo:
GPGPGPU: Evaluation of Parallelisation of Genetic Programming Using GPGPU. SSBSE 2017: 137-142
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