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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SS | 2025-03-10 10:45 |
Kagoshima | (Kagoshima) | Investigating the generalization and robustness performance of CNN models when using RAdam Yusuke Yasuda, Kozo Okano, shinpei Ogata (SU), Shin Nakajima (NII) |
[more] | |
| SS | 2025-03-10 17:20 |
Kagoshima | (Kagoshima) | A Multiple-Choice Testing Approach and the Effect of Temperature Tatsuto Ota, Kozo Okano, Shinpei Ogata (Shinshu Univ), Shin Nakajima (NII) |
[more] | |
| MSS, SS | 2025-01-12 11:15 |
Kagoshima | (Kagoshima) | Automatic Translation from PlantUML description to NuSMV using LLM Kansei Inoue, Takeki Ninomiya, Shinpei Ogata, Kozo Okano (Shinshu Univ)  MSS2024-45 SS2024-24 |
The creation of state transition diagrams and the description of model checking formulas require advanced expertise． Thi... [more] | MSS2024-45 SS2024-24 pp.19-24 |
| DC, SS | 2024-10-17 16:20 |
Shizuoka | (Shizuoka) | Consideration of sentiment analysis for products in an upstream process in software development as a university exercise task. Takumi Katsuie, Shinpei Ogata, Kozo Okano (Shinshu Univ.), Yukako Imura, Shinobu Saito (NTT) SS2024-20 DC2024-48 |
This technical report introduces the results of sentiment analysis of artifacts in requirements engineering phase. These... [more] | SS2024-20 DC2024-48 pp.34-39 |
| KBSE, SS, IPSJ-SE [detail] | 2024-07-25 14:00 |
Hokkaido | (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Privacy protection of training datasets in CNN transfer learning models Takumi Katsuie, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2024-1 KBSE2024-7 |
Transfer learning, one of the machine learning methods, has attracted attention as a technique that can create highly ac... [more] | SS2024-1 KBSE2024-7 pp.1-6 |
| KBSE, SS, IPSJ-SE [detail] | 2024-07-25 14:30 |
Hokkaido | (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Debugging and testing of training datasets using internal activation states of CNN models Daichi Ofuchi, Takumi Katsuie, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2024-2 KBSE2024-8 |
Recently, Artificial Intelligence (AI) and machine learning technologies have made great achievements in various fields.... [more] | SS2024-2 KBSE2024-8 pp.7-12 |
| SWIM, KBSE | 2024-05-17 15:45 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Tokyo, Online) (Primary: On-site, Secondary: Online) |
A Tool for Use Case Driven Modeling of Screen Transitions Yaojun Guo, Shinpei Ogata, Kozo Okano (Shinshu Univ.) KBSE2024-3 SWIM2024-3 |
In the requirements analysis phase of a system involving User Interface (UI), the following activities are often conduct... [more] | KBSE2024-3 SWIM2024-3 pp.13-18 |
| KBSE | 2024-03-14 13:45 |
Okinawa | Okinawa Prefectual General Welfare Center (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Consideration on System Safety Verification Based on User Personality Traits Ruka Narisawa, Shinpei Ogata (Shinshu Univ.), Yoshitaka Aoki (BIPROGY), Hiroyuki Nakagawa (Osaka Univ.), Kazuki Kobayashi, Kozo Okano (Shinshu Univ.) KBSE2023-72 |
(To be available after the conference date) [more] | KBSE2023-72 pp.43-48 |
| KBSE | 2024-03-14 15:15 |
Okinawa | Okinawa Prefectual General Welfare Center (Okinawa, Online) (Primary: On-site, Secondary: Online) |
A Method to Create Scenario by Large Language Model for Input Amount Simulation Yusuke Koyama, Shinpei Ogata, Kozo Okano (Shinshu Univ.) KBSE2023-75 |
One of the means to reasonably reduce the burden of user input to the UI (User Interface) is to introduce usability-enha... [more] | KBSE2023-75 pp.61-66 |
| SS, DC | 2023-10-11 14:55 |
Nagano | (Nagano, Online) (Primary: On-site, Secondary: Online) |
Comparison of Automatic Extraction Methods for Generating Causal Component Models from Software Requirement Specifications Takeki Ninomiya, Masanosuke Ohto, Toshiki Takaoka, Shinpei Ogata, Kozo Okano (Shinshu Univ) SS2023-22 DC2023-28 |
In software development, development proceeds using requirement specifications that describe software requirements in na... [more] | SS2023-22 DC2023-28 pp.7-12 |
| SS, DC | 2023-10-11 15:20 |
Nagano | (Nagano, Online) (Primary: On-site, Secondary: Online) |
Efficient Automatic Classification of Non-Functional Requirements in Information Systems Using Deep Learning
-- A Comparative Accuracy Analysis between BERT and GPT-2 -- Kazuhiro Mukaida (Shinshu Univ.), Seiji Fukui, Takeshi Nagaoka, Takayuki Kitagawa (TOSHIBA), Shinpei Ogata, Kozo Okano (Shinshu Univ.) SS2023-23 DC2023-29 |
Recent Advancements in deep learning are increasingly enabling the automation of classifying non-functional requirements... [more] | SS2023-23 DC2023-29 pp.13-18 |
| SS, DC | 2023-10-12 10:25 |
Nagano | (Nagano, Online) (Primary: On-site, Secondary: Online) |
Robustness trends of DP-SGD, a machine learning with differential privacy Takahiro Kanki, Shinpei Ogata, Kozo Okano (Sinshu Univ), Shin Nakajima (NII) SS2023-28 DC2023-34 |
Although machine learning has been successful in various fields, there is a problem that an adversary can extract traini... [more] | SS2023-28 DC2023-34 pp.38-43 |
| SWIM, KBSE | 2023-05-20 14:25 |
Shizuoka | (Shizuoka, Online) (Primary: On-site, Secondary: Online) |
A Study on Identifying Occurrence of User's Forgetting to Take Items from Interactive Systems Ruka Narisawa, Shinpei Ogata (Shinshu Univ.), Yoshitaka Aoki (BIPROGY), Hiroyuki Nakagawa (Osaka Univ.), Kazuki Kobayashi, Kozo Okano (Shinshu Univ.) KBSE2023-10 SWIM2023-10 |
(To be available after the conference date) [more] | KBSE2023-10 SWIM2023-10 pp.59-64 |
| SS | 2023-03-14 11:50 |
Okinawa | (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Temporal relation identification toward generating temporal logic formulas Maiko Onishi (Ochanomizu Univ.), Shinpei Ogata, Kozo Okano (Shinshu Univ.), Daisuke Bekki (Ochanomizu Univ.) SS2022-49 |
There is room to utilize temporal relations in relation extraction that is incorporated in the analysis of requirements ... [more] | SS2022-49 pp.13-18 |
| SS | 2023-03-15 13:45 |
Okinawa | (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Improvement of Encoding and Ablation Methods in Fault Localization by Ablation Takuma Ikeda, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2022-67 |
Spectrum-based Fault Localization (SFL) is a technique to locate faults in source code using execution traces. A method ... [more] | SS2022-67 pp.121-126 |
| DC, SS | 2022-10-25 14:15 |
Fukushima | (Fukushima, Online) (Primary: On-site, Secondary: Online) |
Relationship between the Defects in Learning Programs and the Model Distortion on the Convolutional Neural Networks Takumi Tsuchiya, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2022-26 DC2022-32 |
In recent years, the quality issue of machine learning software has become an important concern. When considering the qu... [more] | SS2022-26 DC2022-32 pp.23-28 |
| DC, SS | 2022-10-25 14:40 |
Fukushima | (Fukushima, Online) (Primary: On-site, Secondary: Online) |
Comparison of the Coverage Indicators of Evaluation Data for the Convolutional Neural Networks Yuto Yokoyama, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakazima (NII) SS2022-27 DC2022-33 |
Neuron Coverage (NC) was proposed as a measure to quantify the usefulness of evaluation data against Deep Neural Network... [more] | SS2022-27 DC2022-33 pp.29-34 |
| SS, IPSJ-SE, KBSE [detail] | 2022-07-29 16:50 |
Hokkaido | Hokkaido-Jichiro-Kaikan (Sapporo) (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
A Tentative Method to Automatically Generate Logs for Analyzing Relations between Configurations and Logs for Docker-based Web Application Hiroki Kasai (Shinshu Univ.), Satoshi Yazawa (VR), Shinpei Ogata, Kozo Okano (Shinshu Univ.) SS2022-17 KBSE2022-27 |
[more] | SS2022-17 KBSE2022-27 pp.97-102 |
| SS | 2022-03-07 11:20 |
Online | Online (Online) | Trace Ablation and Fault Localization per Method Using Machine Learning Models for Automatic Classification of Test Execution Results Takuma Ikeda, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) SS2021-44 |
The problem to solve automatically classifying the results of test executions is called the test oracle problem. This is... [more] | SS2021-44 pp.13-18 |
| SS, MSS | 2022-01-12 09:15 |
Nagasaki | Nagasakiken-Kensetsu-Sogo-Kaikan Bldg. (Nagasaki, Online) (Primary: On-site, Secondary: Online) |
Execution-trace embedding using word-proximity metric for a method to automatically classify test results Takuma Ikeda, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII) MSS2021-46 SS2021-33 |
The problem to solve automatically classifying the results of test executions is called the test oracle problem. This is... [more] | MSS2021-46 SS2021-33 pp.83-88 |
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