{"id":209659,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00209659","sets":["1164:1384:10524:10525"]},"path":["10525"],"owner":"44499","recid":"209659","title":["RNNの抽象化モデルに対するバグ限局とその評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-02-22"},"_buckets":{"deposit":"5a20d17e-5331-46c1-996f-0636354e2f9c"},"_deposit":{"id":"209659","pid":{"type":"depid","value":"209659","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"RNNの抽象化モデルに対するバグ限局とその評価","author_link":["529108","529109","529107","529110"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"RNNの抽象化モデルに対するバグ限局とその評価"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"デバッグとプログラム自動修正","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学"},{"subitem_text_value":"九州大学"},{"subitem_text_value":"九州大学"},{"subitem_text_value":"九州大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/209659/files/IPSJ-SE21207002.pdf","label":"IPSJ-SE21207002.pdf"},"date":[{"dateType":"Available","dateValue":"2023-02-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SE21207002.pdf","filesize":[{"value":"998.5 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":"378532d9-5b38-4f0b-9e13-7945cf26e6cf","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"石本, 優太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松井, 健"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鵜林, 尚靖"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"亀井, 靖高"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112981","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8825","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，深層学習モデルを取り入れたシステムの開発が広がっており，安全性向上のため，深層学習モデルのバグ（誤動作）の原因を特定する研究が行われている．しかし，既存研究の多くは画像処理を扱う深層学習モデルを対象としており，自然言語処理などを行うRNN（Recurrent Neural Network）を対象とした研究はあまり行われていない．そこで本研究では，RNN を対象として間接的にバグの原因を特定する手法を提案する．具体的には，RNN を抽象化した確率モデルを抽出し，そのモデルに対してプログラムのバグ限局（Fault Localization）の手法を応用する．初期実験として，映画レビュー文や人工言語のデータセットを用いて，抽出した確率モデルに対するバグ限局により RNN のバグの原因を効果的に特定できるかを評価した．その結果，提案手法のバグ限局を利用することで，RNN のバグに関係するデータを訓練データから抽出できることが明らかになった．映画レビュー文のデータセットについては，抽出したデータの精度はランダムに選んだデータよりも平均で 19% 低い．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ソフトウェア工学（SE）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2021-SE-207"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T18:26:53.403890+00:00","created":"2025-01-19T01:10:57.249695+00:00","links":{}}