{"updated":"2025-01-21T18:56:02.643419+00:00","links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00082616","sets":["581:6644:6801"]},"path":["6801"],"owner":"11","recid":"82616","title":["開発履歴メトリクスを用いた細粒度なFault-proneモジュール予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-06-15"},"_buckets":{"deposit":"8042ed41-503b-4dee-abf3-97c3c0276a7d"},"_deposit":{"id":"82616","pid":{"type":"depid","value":"82616","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"開発履歴メトリクスを用いた細粒度なFault-proneモジュール予測","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"開発履歴メトリクスを用いた細粒度なFault-proneモジュール予測"},{"subitem_title":"Fault-prone Module Prediction on Fine-grained Modules Based on Historical Metrics","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[一般論文] Fault-proneモジュール予測，細粒度予測，細粒度マイニング，開発履歴メトリクス，工数を考慮した評価","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2012-06-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"大阪大学大学院情報科学研究科"},{"subitem_text_value":"京都工芸繊維大学大学院工芸科学研究科"},{"subitem_text_value":"大阪大学大学院情報科学研究科"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Technology, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Technology, Kyoto Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Technology, Osaka University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/82616/files/IPSJ-JNL5306019.pdf"},"date":[{"dateType":"Available","dateValue":"2014-06-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL5306019.pdf","filesize":[{"value":"613.4 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":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"211530b1-4a1e-4b64-8fb4-04979da0c994","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2012 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"畑, 秀明"},{"creatorName":"水野, 修"},{"creatorName":"菊野, 亨"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hideaki, Hata","creatorNameLang":"en"},{"creatorName":"Osamu, Mizuno","creatorNameLang":"en"},{"creatorName":"Tohru, Kikuno","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Fault-proneモジュールの予測において，ソフトウェアリポジトリから収集可能な開発履歴メトリクスは有用であることが数多くの文献で報告されている．開発履歴メトリクスには，コードに関するもの，プロセスに関するもの，開発組織に関するものなどがある．これらのメトリクスの収集はファイルレベルでは容易であるが，より細粒度なメソッドレベルでは収集が困難であった．これは，版管理システムがソースコードをファイルレベルで管理するためである．本稿では，以前に提案した細粒度履歴管理リポジトリを用いることでメソッドレベルの開発履歴メトリクスの収集を行う．オープンソースソフトウェアプロジェクトを対象に開発履歴メトリクスを細粒度モジュール（メソッドレベル）とファイルレベルで収集し，Fault-proneモジュール予測を行った．工数を考慮した評価から，細粒度モジュールでのFault-proneモジュール予測がファイルレベルに比べて有用であることを確認した．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Many studies reported that historical metrics collected from software repositories are useful for fault-prone module prediction. There are many historical metrics proposed in literature, such as code-related, process-related, and organization-related metrics. Since source code management system stored file-level histories, it has been difficult to collect historical metrics of fine-grained modules compared to file-level historical metrics. Using our fine-grained version control system, this paper conducts a comparative study of fault-prone module prediction on a file-level and a method-level. We empirically evaluated our prediction models with open source software projects. Based on effort-aware models, fault-prone module prediction models on fine-grained modules perform better than file-level models.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1643","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"1635","bibliographicIssueDates":{"bibliographicIssueDate":"2012-06-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"53"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":82616,"created":"2025-01-18T23:36:27.280248+00:00"}