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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SS, DC | 2023-10-11 14:55 |
Nagano | (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 | (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 | (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 | (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 | (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 | (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 | (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 | (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) (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 | 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. (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 |
| KBSE, SC | 2021-11-05 13:50 |
Online | Online + Morioka City (KBSE) (Primary: Online, Secondary: On-site) |
Quantitative evaluation effectiveness and efficiency of UI pattern for cataloging Yu Saitou, Shinpei Ogata, Kozo Okano (Shinshu Univ.) KBSE2021-25 SC2021-24 |
In web application development, developers use what to implement in the UI (user interface) patterns at the design stage... [more] | KBSE2021-25 SC2021-24 pp.1-6 |
| KBSE, IPSJ-SE, SS [detail] | 2021-07-08 13:25 |
Online | Online (Zoom) | Proposal of a form of requirement specifications for automatic transition model derivation and the derivation method Hiroya Ii, Masanosuke Ohto, Hitoshi Kiryu, Shinpei Ogata, Kozo Okano (Shinshu Univ.) SS2021-3 KBSE2021-15 |
[more] | SS2021-3 KBSE2021-15 pp.13-18 |
| KBSE, IPSJ-SE, SS [detail] | 2021-07-08 14:15 |
Online | Online (Zoom) | Extraction method for transition relations from conditional statements in natural language requirements specifications Maiko Onishi (Ochanomizu Univ.), Hiroya Ii, Shinpei Ogata, Kozo Okano (Shinshu Univ.), Daisuke Bekki (Ochanomizu Univ.) SS2021-5 KBSE2021-17 |
In software development, it is generally known that detecting defects at an early stage of the process reduces rework an... [more] | SS2021-5 KBSE2021-17 pp.25-30 |
| KBSE, SWIM | 2021-05-21 11:00 |
Online | Online | Implementation of Software Edutainment Systems and Analysis of Learners' Data Ryosuke Tsutsumi, Wei JiuJun, Shinpei Ogata, Masaaki Niimura, Kozo Okano (Shinshu Univ) KBSE2021-1 SWIM2021-1 |
[more] | KBSE2021-1 SWIM2021-1 pp.1-6 |
| KBSE, SWIM | 2021-05-22 14:00 |
Online | Online | An Automated Method of Identifying Errors in UML State Machine Diagrams for Generating Educational Feedback
-- Focus on the Types of Errors to Be Identified and the Results of Their Identification -- Mitsutada Goshima, Shinpei Ogata (Shinshu Univ.), Erina Makihara (Doshisha Univ.), Kozo Okano (Shinshu Univ.) KBSE2021-10 SWIM2021-10 |
In learning UML (Unified Modeling Language) state machine diagrams, it is difficult for learners to receive quick educat... [more] | KBSE2021-10 SWIM2021-10 pp.56-61 |
| NS | 2021-04-16 13:50 |
Online | Online | A Metamodel for Network Configuration Information Nagi Arai, Hikofumi Suzuki, Shinpei Ogata, Kozo Okano (Shinshu Univ) NS2021-14 |
In terms of communication protocols and network device configuration information used at the Layer 3 level and above, it... [more] | NS2021-14 pp.77-82 |
| KBSE | 2021-03-05 13:35 |
Online | Online | A Method to Visualize Log Files for Analyzing Unexpected Behavior of Web Applications Hiroki Kasai (Shinshu Univ), Satoshi Yazawa (VR), Shinpei Ogata, Kozo Okano (Shinshu Univ) KBSE2020-35 |
In order for developers and maintainers to understand the situation in which their Web applications behaved unexpectedly... [more] | KBSE2020-35 pp.7-12 |
| SS | 2021-03-04 13:25 |
Online | Online | Generating Exhaustive Counterexample and Path Constraint with Software Analysis Workbench and Symbolic PathFinder Rin Karashima, Shinpei Ogata, Kozo Okano (Shinshu Univ.) SS2020-41 |
Software Analysis Workbench (SAW) generates models from JVM bytecode by symbolic execution. Users can perform model che... [more] |
SS2020-41 pp.78-83 |
| KBSE, SC | 2020-11-13 15:00 |
Online | Online + Kikai-Shinko-Kaikan Bldg. (Primary: Online, Secondary: On-site) |
KBSE2020-13 SC2020-17 |
In order to support the education of UML state machine diagrams, studies are being carried out to analyze learners' erro... [more] | KBSE2020-13 SC2020-17 p.26 |
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