Mobile Application Software Defect Prediction

被引：11

作者：

Ricky, Michael Yoseph ^{[1
]}

Yulianto, Budi ^{[1
]}

Purnomo, Fredy ^{[1
]}

机构：

[1] Bina Nusantara Univ, Comp Sci, Jakarta, Indonesia

来源：

PROCEEDINGS 2016 IEEE SYMPOSIUM ON SERVICE-ORIENTED SYSTEM ENGINEERING SOSE 2016 | 2016年

关键词：

CART; test metrics; defect prediction; mobile apps; software defect; SVM; FAULT PREDICTION;

D O I：

10.1109/SOSE.2016.25

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

the increasing number of user of mobile application, it is needed to check mobile applications that contains defect or not. I proposed a SVM method in comparison with CART and Test Metrics to classify classes in application. It shows that SVM method has better result in terms of precision and accuracy. SVM accuracy reaches 83% compared with CART and Test Metrics method in mobile apps defect prediction.

引用

页码：307 / 313

页数：7

共 21 条

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