Presentation 2016-07-15
Investigation Strategies and Relevance Metric on Dynamic Feature Location
Maaki Nakano, Shinpei Hayashi, Takashi Kobayashi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In dynamic feature location based on formal concept analysis, it is a hard problem that modules implementing focused feature distribute dispersively among many formal concepts. For this reason, in locating, users must investigate many formal concepts. To improve the efficiency of this feature location technique, we propose two investigation strategies using a relevance metric. We use a similarity that is used in area of fault localization as a relevance metric. We applied our investigation strategies to several features of a representative open source software product and compared them with an existing strategy.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Dynamic Feature Location / Formal Concept Analysis
Paper # SS2016-17,KBSE2016-23
Date of Issue 2016-07-06 (SS, KBSE)

Conference Information
Committee KBSE / SS / IPSJ-SE
Conference Date 2016/7/13(3days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Shigeo Kaneda(Doshisha Univ.) / Kazuhiro Ogata(JAIST)
Vice Chair Fumihiro Kumeno(Nippon Inst. of Tech.) / Akio Nakata(Hiroshima City Univ.)
Secretary Fumihiro Kumeno(Shinshu Univ.) / Akio Nakata(Nippon Inst. of Tech.) / (Tokyo Inst. of Tech.)
Assistant Hajime Iwata(Kanagawa Inst. of Tech.) / Kohei Sakurai(Kanazawa Univ.) / Kazuyuki Shima(Hiroshima City Univ.)

Paper Information
Registration To Technical Committee on Knowledge-Based Software Engineering / Technical Committee on Software Science / Special Interest Group on Software Engineering
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Investigation Strategies and Relevance Metric on Dynamic Feature Location
Sub Title (in English)
Keyword(1) Dynamic Feature Location
Keyword(2) Formal Concept Analysis
1st Author's Name Maaki Nakano
1st Author's Affiliation Tokyo Insitute of Technology(Tokyo Tech.)
2nd Author's Name Shinpei Hayashi
2nd Author's Affiliation Tokyo Insitute of Technology(Tokyo Tech.)
3rd Author's Name Takashi Kobayashi
3rd Author's Affiliation Tokyo Insitute of Technology(Tokyo Tech.)
Date 2016-07-15
Paper # SS2016-17,KBSE2016-23
Volume (vol) vol.116
Number (no) SS-127,KBSE-128
Page pp.pp.169-174(SS), pp.169-174(KBSE),
#Pages 6
Date of Issue 2016-07-06 (SS, KBSE)