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タマダ ハルアキ
TAMADA HARUAKI
玉田 春昭 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2007 |
| 形態種別 | その他 |
| 標題 | Mining Quantitative Rules in a Software Project Data Set |
| 執筆形態 | その他 |
| 掲載誌名 | Information and Media Technologies |
| 出版社・発行元 | Information and Media Technologies Editorial Board |
| 巻・号・頁 | 2(4),pp.999-1008 |
| 著者・共著者 | Morisaki Shuji,Monden Akito,Tamada Haruaki,Matsumura Tomoko,Matsumoto Ken-ichi |
| 概要 | 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. |
| DOI | 10.11185/imt.2.999 |
| NAID | 130000058243 |