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Mining Quantitative Rules in a Software Project Data Set
https://ipsj.ixsq.nii.ac.jp/records/9871
https://ipsj.ixsq.nii.ac.jp/records/9871098e5214-89aa-444a-8add-cc6e8864ef86
名前 / ファイル | ライセンス | アクション |
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Copyright (c) 2007 by the Information Processing Society of Japan
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オープンアクセス |
Item type | Journal(1) | |||||||
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公開日 | 2007-08-15 | |||||||
タイトル | ||||||||
タイトル | Mining Quantitative Rules in a Software Project Data Set | |||||||
タイトル | ||||||||
言語 | en | |||||||
タイトル | Mining Quantitative Rules in a Software Project Data Set | |||||||
言語 | ||||||||
言語 | eng | |||||||
キーワード | ||||||||
主題Scheme | Other | |||||||
主題 | 特集:ソフトウェア工学の理論と実践 | |||||||
資源タイプ | ||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||
資源タイプ | journal article | |||||||
その他タイトル | ||||||||
その他のタイトル | 開発支援環境・自動化技術 | |||||||
著者所属 | ||||||||
Graduate School of Information Science Nara Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Graduate School of Information Science Nara Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Graduate School of Information Science Nara Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Graduate School of Information Science Nara Institute of Science and Technology | ||||||||
著者所属 | ||||||||
Graduate School of Information Science Nara Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Graduate School of Information Science, Nara Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Graduate School of Information Science, Nara Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Graduate School of Information Science, Nara Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Graduate School of Information Science, Nara Institute of Science and Technology | ||||||||
著者所属(英) | ||||||||
en | ||||||||
Graduate School of Information Science, Nara Institute of Science and Technology | ||||||||
著者名 |
Shuji, Morisaki
Akito, Monden
Haruaki, Tamada
Tomoko, Matsumura
Ken-ichiMatsumoto
× Shuji, Morisaki Akito, Monden Haruaki, Tamada Tomoko, Matsumura Ken-ichiMatsumoto
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著者名(英) |
Shuji, Morisaki
Akito, Monden
Haruaki, Tamada
Tomoko, Matsumura
Ken-ichi, Matsumoto
× Shuji, Morisaki Akito, Monden Haruaki, Tamada Tomoko, Matsumura Ken-ichi, Matsumoto
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論文抄録 | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | This paper proposes a method to mine rules from a software project data set that contains a number of quantitative attributes such as staff months and SLOC. The proposed method extends conventional association analysis methods to treat quantitative variables in two ways: (1) the distribution of a given quantitative variable is described in the consequent part of a rule by its mean value and standard deviation so that conditions producing the distinctive distributions can be discovered. To discover optimized conditions (2) quantitative values appearing in the antecedent part of a rule are divided into contiguous fine-grained partitions in preprocessing then rules are merged after mining so that adjacent partitions are combined. The paper also describes a case study using the proposed method on a software project data set collected by Nihon Unisys Ltd. In this case the method mined rules that can be used for better planning and estimation of the integration and system testing phases along with criteria or standards that help with planning of outsourcing resources. | |||||||
論文抄録(英) | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | This paper proposes a method to mine rules from a software project data set that contains a number of quantitative attributes such as staff months and SLOC. The proposed method extends conventional association analysis methods to treat quantitative variables in two ways: (1) the distribution of a given quantitative variable is described in the consequent part of a rule by its mean value and standard deviation so that conditions producing the distinctive distributions can be discovered. To discover optimized conditions, (2) quantitative values appearing in the antecedent part of a rule are divided into contiguous fine-grained partitions in preprocessing, then rules are merged after mining so that adjacent partitions are combined. The paper also describes a case study using the proposed method on a software project data set collected by Nihon Unisys Ltd. In this case, the method mined rules that can be used for better planning and estimation of the integration and system testing phases, along with criteria or standards that help with planning of outsourcing resources. | |||||||
書誌レコードID | ||||||||
収録物識別子タイプ | NCID | |||||||
収録物識別子 | AN00116647 | |||||||
書誌情報 |
情報処理学会論文誌 巻 48, 号 8, p. 2725-2734, 発行日 2007-08-15 |
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ISSN | ||||||||
収録物識別子タイプ | ISSN | |||||||
収録物識別子 | 1882-7764 |