| Project/Area Number |
15H02683
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Software
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
林 晋平 東京工業大学, 情報理工学院, 准教授 (40541975)
石尾 隆 奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (60452413)
渥美 紀寿 京都大学, 学術情報メディアセンター, 助教 (70397446)
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| Research Collaborator |
Noda Kunihiro
Aizawa Yuya
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥18,070,000 (Direct Cost: ¥13,900,000、Indirect Cost: ¥4,170,000)
Fiscal Year 2018: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2017: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2016: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2015: ¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
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| Keywords | ソフトウェア工学 / ソフトウェア保守 / プログラム理解 / リバースエンジニアリング / ソフトウェア学 |
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| Outline of Final Research Achievements |
In this research, we aim to support program comprehension during software maintenance and develop methods to identify and visualize the relationship between external and internal features.
We proposed a dynamic feature location technique (DFLT) using the formal concept analysis to identify relationships between modules and features. We use the similarity coefficient, which is used in fault localization techniques, as a relationship. Our DFLT make better orders shared modules compared with an existing DFLT. We also proposed a fully automated technique for recovering a summarized sequence diagram of a reasonable size. The recovered diagram depicts a behavioral overview of important concepts in a subject system, which can support developers to comprehend external features in an early stage of program comprehension. Our developed visualization tool is a flexible and lightweight tool and enable to explore a massive-scale sequence diagram by using searching, grouping and folding features.
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| Academic Significance and Societal Importance of the Research Achievements |
外的機能と内的機能に着目して機能識別を支援するという体系化を行っており，動的な機能識別と欠陥箇所特定手法を応用した新しい手法を開発しており，外的機能と内的機能の関係識別の精度を改善できることを示した点と，重要オブジェクトの特定と静的構造特徴に基づくグループ化を行うことで動的情報に対して段階的詳細化を行う手段を確立した点，実用規模のソフトウェアに対してその有効性を明らかにした点は学術的に意義があるものと考える．
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