| 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)
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| 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.
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