کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
461772 696631 2008 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting defect-prone software modules using support vector machines
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
Predicting defect-prone software modules using support vector machines
چکیده انگلیسی

Effective prediction of defect-prone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Support vector machines (SVM) have been successfully applied for solving both classification and regression problems in many applications. This paper evaluates the capability of SVM in predicting defect-prone software modules and compares its prediction performance against eight statistical and machine learning models in the context of four NASA datasets. The results indicate that the prediction performance of SVM is generally better than, or at least, is competitive against the compared models.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Systems and Software - Volume 81, Issue 5, May 2008, Pages 649–660
نویسندگان
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