{"created":"2025-01-19T01:28:54.181056+00:00","updated":"2025-01-19T11:28:56.760797+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229631","sets":["6504:11436:11438"]},"path":["11438"],"owner":"44499","recid":"229631","title":["発生頻度の少ないコーディング規約違反データ統合による検出精度向上への試み"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"18cdf711-0348-41d1-83c9-bc74c82262dc"},"_deposit":{"id":"229631","pid":{"type":"depid","value":"229631","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"発生頻度の少ないコーディング規約違反データ統合による検出精度向上への試み","author_link":["617681","617678","617680","617679"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"発生頻度の少ないコーディング規約違反データ統合による検出精度向上への試み"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソフトウェア科学・工学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"和歌山大"},{"subitem_text_value":"和歌山大"},{"subitem_text_value":"和歌山大"},{"subitem_text_value":"和歌山大"}]},"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/229631/files/IPSJ-Z85-5K-01.pdf","label":"IPSJ-Z85-5K-01.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-5K-01.pdf","filesize":[{"value":"354.6 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"5ef363d0-e34c-40a1-bfdd-989eca9814ed","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"亀岡, 令"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"伊原, 彰紀"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"南, 雄太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大森, 楓己"}],"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"規約違反自動検出ツールは，高品質を保証するために膨大な規約違反を検出するが，開発者は全て修正することはない．従来研究では開発者が優先的に修正すべき規約を特定するための機械学習モデルを構築している．しかし，機械学習の検出精度は学習データセットサイズに依存し，規約によって発生数，修正率に偏りがあるため，修正すべき規約を検出するだけの十分なデータを収集できないことも多い．本研究では，違反数の少ない複数の規約を混合して学習させることで，学習データセットサイズが小さい場合の違反検出精度の向上を目指す．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"204","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"203","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229631,"links":{}}