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ORCIDSusumu Tokumoto
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2020 – today
- 2023
[c18]Satoshi Munakata, Susumu Tokumoto, Koji Yamamoto, Kazuki Munakata:
Towards Formal Repair and Verification of Industry-scale Deep Neural Networks. ICSE Companion 2023: 360-364- [c17]Takao Nakagawa, Susumu Tokumoto, Shogo Tokui, Fuyuki Ishikawa:
An Experience Report on Regression-Free Repair of Deep Neural Network Model. SANER 2023: 778-782 - 2022
- [c16]Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa:
Practical insights of repairing model problems on image classification. CAIN 2022: 157-158 - [c15]Shogo Tokui, Susumu Tokumoto, Akihito Yoshii, Fuyuki Ishikawa, Takao Nakagawa, Kazuki Munakata, Shinji Kikuchi:
NeuRecover: Regression-Controlled Repair of Deep Neural Networks with Training History. SANER 2022: 1111-1121 - [i3]Shogo Tokui, Susumu Tokumoto, Akihito Yoshii, Fuyuki Ishikawa, Takao Nakagawa, Kazuki Munakata, Shinji Kikuchi:
NeuRecover: Regression-Controlled Repair of Deep Neural Networks with Training History. CoRR abs/2203.00191 (2022) - [i2]Akihito Yoshii, Susumu Tokumoto, Fuyuki Ishikawa:
Practical Insights of Repairing Model Problems on Image Classification. CoRR abs/2205.07116 (2022) - [i1]Zhijie Wang, Yuheng Huang, Lei Ma, Haruki Yokoyama, Susumu Tokumoto, Kazuki Munakata:
An Exploratory Study of AI System Risk Assessment from the Lens of Data Distribution and Uncertainty. CoRR abs/2212.06828 (2022) - 2020
- [j2]Gaku Fujii, Koichi Hamada, Fuyuki Ishikawa, Satoshi Masuda, Mineo Matsuya, Tomoyuki Myojin, Yasuharu Nishi, Hideto Ogawa, Takahiro Toku, Susumu Tokumoto, Kazunori Tsuchiya, Yasuhiro Ujita:
Guidelines for Quality Assurance of Machine Learning-Based Artificial Intelligence. Int. J. Softw. Eng. Knowl. Eng. 30(11&12): 1589-1606 (2020) - [c14]Henri Trenquier, Fuyuki Ishikawa, Susumu Tokumoto:
Attribute-based Granular Evaluation for Performance of Machine Learning Models. AITest 2020: 125-132 - [c13]Koichi Hamada, Fuyuki Ishikawa, Satoshi Masuda, Tomoyuki Myojin, Yasuharu Nishi, Hideto Ogawa, Takahiro Toku, Susumu Tokumoto, Kazunori Tsuchiya, Yasuhiro Ujita, Mineo Matsuya:
Guidelines for Quality Assurance of Machine Learning-based Artificial Intelligence. SEKE 2020: 335-341
2010 – 2019
- 2019
- [c12]Masaki Hosono, Susumu Tokumoto, Supasit Monpratarnchai, Hironori Washizaki, Kiyoshi Honda, Hiromasa Nagumo, Hisanobu Sonoda, Yoshiaki Fukazawa, Kazuki Munakata, Takao Nakagawa, Yusuke Nemoto:
Inappropriate Usage Examples in Web API Documentations. ICSME 2019: 343-347 - [c11]Susumu Tokumoto, Kuniharu Takayama:
PHANTA: Diversified Test Code Quality Measurement for Modern Software Development. ASE 2019: 1206-1207 - [c10]Yutaka Matsuno, Fuyuki Ishikawa
, Susumu Tokumoto:
Tackling Uncertainty in Safety Assurance for Machine Learning: Continuous Argument Engineering with Attributed Tests. SAFECOMP Workshops 2019: 398-404 - 2018
- [c9]Ripon K. Saha, Hiroaki Yoshida, Mukul R. Prasad, Susumu Tokumoto, Kuniharu Takayama, Isao Nanba:
Elixir: an automated repair tool for Java programs. ICSE (Companion Volume) 2018: 77-80 - 2017
- [j1]Hiroaki Yoshida, Guodong Li, Takuki Kamiya, Indradeep Ghosh, Sreeranga P. Rajan, Susumu Tokumoto, Kazuki Munakata, Tadahiro Uehara:
KLOVER: Automatic Test Generation for C and C Programs, Using Symbolic Execution. IEEE Softw. 34(5): 30-37 (2017) - 2016
- [c8]Susumu Tokumoto, Hiroaki Yoshida, Kazunori Sakamoto, Shinichi Honiden:
MuVM: Higher Order Mutation Analysis Virtual Machine for C. ICST 2016: 320-329 - [c7]Hiroaki Yoshida, Susumu Tokumoto, Mukul R. Prasad, Indradeep Ghosh, Tadahiro Uehara:
FSX: fine-grained incremental unit test generation for C/C++ programs. ISSTA 2016: 106-117 - [c6]Hiroaki Yoshida, Susumu Tokumoto, Mukul R. Prasad, Indradeep Ghosh, Tadahiro Uehara:
FSX: a tool for fine-grained incremental unit test generation for C/C++ programs. SIGSOFT FSE 2016: 1052-1056 - 2014
- [c5]Susumu Tokumoto, Kazunori Sakamoto, Kiyofumi Shimojo, Tadahiro Uehara, Hironori Washizaki:
Semi-automatic Incompatibility Localization for Re-engineered Industrial Software. ICST 2014: 91-94 - 2013
- [c4]Kazuki Munakata, Susumu Tokumoto, Tadahiro Uehara:
Model-based test case generation using symbolic execution. JAMAICA@ISSTA 2013: 23-28 - 2012
- [c3]Susumu Tokumoto, Tadahiro Uehara, Kazuki Munakata, Haruyuki Ishida, Toru Eguchi, Masafumi Baba:
Enhancing Symbolic Execution to Test the Compatibility of Re-engineered Industrial Software. APSEC 2012: 314-317 - [c2]Kazuki Munakata, Shoichiro Fujiwara, Susumu Tokumoto, Tadahiro Uehara:
Test Case Selection Based on Path Condtions of Symbolic Execution. APSEC 2012: 318-321 - [c1]Yoshihide Nomura, Kosaku Kimura, Hidetoshi Kurihara, Rieko Yamamoto, Kouji Yamamoto, Susumu Tokumoto:
Massive Event Data Analysis and Processing Service Development Environment Using DFD. SERVICES 2012: 80-87
Coauthor Index
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