{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212687","sets":["6164:6165:6522:10650"]},"path":["10650"],"owner":"44499","recid":"212687","title":["静的解析によるUMLステートマシン図答案の誤り特定自動化手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-08-30"},"_buckets":{"deposit":"9a189661-ea61-43c1-8c22-72ec817139db"},"_deposit":{"id":"212687","pid":{"type":"depid","value":"212687","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"静的解析によるUMLステートマシン図答案の誤り特定自動化手法の提案","author_link":["543000","542997","542998","542999"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"静的解析によるUMLステートマシン図答案の誤り特定自動化手法の提案"},{"subitem_title":"An Automated Method of Identifying Errors in Learner-Created UML State Machine Diagrams with Static Analysis\\n","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"プログラミング学習・教育","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2021-08-30","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"信州大学工学部"},{"subitem_text_value":"信州大学工学部"},{"subitem_text_value":"同志社大学"},{"subitem_text_value":"信州大学工学部"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Engineering, Shinshu University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Engineering, Shinshu University","subitem_text_language":"en"},{"subitem_text_value":"Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Engineering, Shinshu University","subitem_text_language":"en"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/212687/files/IPSJ-SES2021014.pdf","label":"IPSJ-SES2021014.pdf"},"date":[{"dateType":"Available","dateValue":"2023-08-30"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SES2021014.pdf","filesize":[{"value":"447.0 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"12"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"93180c0d-5849-4576-a6f2-cbf887899aba","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"五島, 光祥"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小形, 真平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"槇原, 絵里奈"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"岡野, 浩三"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"UML（Unified Modeling Language）モデリングの多人数教育では，得られる答案モデルが多数かつ多様になりやすいため，教育者が答案を手動で評価することに時間がかかってしまう．教育者が答案評価を通じてモデルの誤りについて学習者へフィードバックしようとするとき，答案の誤りを正確に把握することが必須である．その支援のために我々はこれまで，正答例に基づき答案の正誤を自動判定する手法を提案してきたが，誤りの箇所や種類の自動特定には至っていない．そこで本稿では，正答例と答案の記述を比較するよう静的解析を行うことで，ステートマシン図の誤り箇所と種類を自動で特定する手法を提案する．提案手法を 57 個の学習者の答案（ステートマシン図）に適用した結果，状態，遷移，実行活動，開始疑似状態，終了状態で構成される答案において正しい特定結果が得られたため，提案手法が有用である見込みを得た．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In teaching UML (Unified Modeling Language) state machine diagrams for many learners, the educators spend much time to evaluate learner-created models since those models are often many and varied. When educators want to make educational feedback on model errors, they firstly should grasp errors in learner-created models accurately. For this purpose, we have proposed a method to support the correctness of answer behavior using example answers. To this end, we have proposed a method to automatically judge the correctness of leaner-created models based on the sample answer model. However, this method still cannot identify locations and types of the errors in the incorrect models. In this paper, we propose a method to automatically identify the location and type of errors in state machine diagrams by statically analyzing the differences between learner-created models and the sample answer model. The proposed method was applied to 57 learner-created models (state machine diagrams), and the results showed that the proposed method is likely to be useful, because the answers, which did not contain expressions with variables, gave correct identification results. ","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"75","bibliographic_titles":[{"bibliographic_title":"ソフトウェアエンジニアリングシンポジウム2021論文集"}],"bibliographicPageStart":"67","bibliographicIssueDates":{"bibliographicIssueDate":"2021-08-30","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212687,"updated":"2025-01-19T17:25:03.663998+00:00","links":{},"created":"2025-01-19T01:13:37.259245+00:00"}