{"id":211812,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00211812","sets":["1164:1384:10524:10618"]},"path":["10618"],"owner":"44499","recid":"211812","title":["機械学習を用いた不吉な臭いの検出における誤分類データの影響"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-07-01"},"_buckets":{"deposit":"46531244-1ed7-4858-990c-64618f14e1f9"},"_deposit":{"id":"211812","pid":{"type":"depid","value":"211812","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習を用いた不吉な臭いの検出における誤分類データの影響","author_link":["538910","538911"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習を用いた不吉な臭いの検出における誤分類データの影響"}]},"item_type_id":"4","publish_date":"2021-07-01","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"立命館大学"},{"subitem_text_value":"立命館大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Ritsumeikan Uniersity","subitem_text_language":"en"},{"subitem_text_value":"Ritsumeikan Uniersity","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/211812/files/IPSJ-SE21208012.pdf","label":"IPSJ-SE21208012.pdf"},"date":[{"dateType":"Available","dateValue":"2023-07-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SE21208012.pdf","filesize":[{"value":"1.0 MB"}],"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":"0659eaad-3c22-4fdb-ac5b-cc52d4be66bd","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":"糀田, 利貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"丸山, 勝久"}],"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":"不格好な実装や設計の欠陥を指すコードの不吉な臭いは，ソースコードの理解を妨げ，さらに変更容易性の低下を招く．リファクタリングは，このようなコードの不吉な臭いを取り除く有力な手段である．リファクタリングとは，既存のプログラムの外部的振る舞いを維持しつつ，その内部構造を改善させる作業を指す．近年，リファクタリング対象の特定を支援するために，機械学習によるコードの不吉な臭いの自動検出の研究が行われている．しかしながら，検出の正確さは十分ではない．我々は，訓練データに含まれる誤分類データが検出の正確さを低下させている原因であると考えた．そこで，12 個の Java プロジェクトに含まれる 7 種類の不吉な臭いに対して，意図的に誤分類データを混入させたり，それらを機械的に除去したりすることで，不吉な臭いの検出の正確さの変化を調査した．その結果，誤分類データが含まれることで，正確さが有意に低下することが分かった．さらに，誤分類データを機械的に除去することが，必ずしも検出の正確さを向上させるとは限らないことも分かった．","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":"2021-07-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"12","bibliographicVolumeNumber":"2021-SE-208"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T17:40:04.687616+00:00","created":"2025-01-19T01:12:56.752450+00:00","links":{}}