{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00186606","sets":["1164:1384:9436:9437"]},"path":["9437"],"owner":"11","recid":"186606","title":["情報検索に基づくBug Localizationへの不吉な臭いの深刻度の利用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-03-02"},"_buckets":{"deposit":"7244933a-b5d3-4e2e-b1a7-025a7914f72d"},"_deposit":{"id":"186606","pid":{"type":"depid","value":"186606","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"情報検索に基づくBug Localizationへの不吉な臭いの深刻度の利用","author_link":["419128","419129","419131","419132","419126","419130","419127","419125"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"情報検索に基づくBug Localizationへの不吉な臭いの深刻度の利用"},{"subitem_title":"Using Code Smell Severity to Improve IR-Based Bug Localization","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"保守","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2018-03-02","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京工業大学"},{"subitem_text_value":"東京工業大学"},{"subitem_text_value":"東京工業大学"},{"subitem_text_value":"東京工業大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","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/186606/files/IPSJ-SE18198016.pdf","label":"IPSJ-SE18198016.pdf"},"date":[{"dateType":"Available","dateValue":"2020-03-02"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-SE18198016.pdf","filesize":[{"value":"519.8 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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":"大規模なソフトウェア開発では，ある特定のバグを解決するために修正すべきソースコード箇所を見つける Bug Localization が必要である．情報検索に基づく Bug Localization 手法 （IR 手法）は，バグに関して記述されたバグレポートとソースコード内のモジュールとのテキスト類似度を計算し，これに基づき修正すべきモジュールを特定する．しかし，この手法は各モジュールのバグの出やすさの度合いを考慮していないため精度が低い．本論文では，ソースコード内のモジュールのバグの出やすさとして不吉な臭いを用い，これを既存の IR 手法と組み合わせた Bug Localization 手法を提案する．提案手法では，不吉な臭いの深刻度と，ベクトル空間モデルに基づくテキスト類似度を統合した新しい評価値を定義している．これは深刻度の高い不吉な臭いとバグレポートとの高いテキスト類似性の両方を持つモジュールを上位に位置付け，バグを解決するために修正すべきモジュールを予測する．4 つの OSS プロジェクトの過去のバグレポートを用いた評価では，いずれのプロジェクト，モジュール粒度においても提案手法の精度が既存の IR 手法を上回り，また最大で 269% の向上がみられた．","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":"2018-03-02","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"16","bibliographicVolumeNumber":"2018-SE-198"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":186606,"updated":"2025-01-20T02:31:24.302597+00:00","links":{},"created":"2025-01-19T00:53:32.883635+00:00"}