Departmental Bulletin Paper 定性的なソフトウェアプロジェクトデータに基づくプロダクト品質予測に関する研究

新井, 雄一朗

This article discusses a method for finding the software development project in which thedeveloped software may cause at least one software failure in its operational phase. For this, we analyze the data sets which were obtained before the test phase as the results of questionnaire from the real domestic software development companies. In particular, the data sets consist of not quantitative variables but qualitative ones. As a result of the actual data analysis, we found that the Random Forests showed better performance against the logistic regression analysis with dummy variables.Key Words : Software reliability, qualitative variable, machine learning, Random Forests

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