Generation of mimic data sets from confidential software project data sets
| Project/Area Number |
17K00102
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Software
|
|---|
| Research Institution | Okayama University |
|---|
Principal Investigator |
Monden Akito 岡山大学, 自然科学研究科, 教授 (80311786)
|
|---|
| Project Period (FY) |
2017-04-01 – 2020-03-31
|
| Project Status |
Completed (Fiscal Year 2019)
|
| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
|---|
| Keywords | データ機密保護 / ソフトウェア開発実績データ / ソフトウェア開発工数予測 / データ分析 / 実証的ソフトウェア工学 / データマイニング / ソフトウエア学 |
|---|
| Outline of Final Research Achievements |
This study proposes a method for artificially generating a mimic software project data set, whose characteristics (related to data distribution and data dependencies) are very similar to a given confidential data set. In this method, companies need to provide only several statistical values of their confidential data. Our experimental evaluation confirmed that the generated mimic data sets can be applied to various data prediction/analysis methods, and, in case that the original data contain enough data points, we could expect obtaining similar prediction/analysis results as the original data set.
|
| Academic Significance and Societal Importance of the Research Achievements |
本研究の成果により，データの機密性を保持したまま，その利活用が可能となることが実証された．提案方法により生成されたデータを広く公開することで，予測モデルの性能評価，ベンチマーキング，データ処理技術の評価等に活用でき，実証的ソフトウェア工学の研究分野の発展に寄与できると期待される．また，提案方法は，機密データを利用する様々な分野への応用が期待される．
|
Report
(4 results)
Research Products
(8 results)
