کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6899071 1446449 2018 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An empirical evaluation of classification algorithms for fault prediction in open source projects
ترجمه فارسی عنوان
ارزیابی تجربی الگوریتم های طبقه بندی برای پیش بینی خطا در پروژه های منبع باز
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی
Creating software with high quality has become difficult these days with the fact that size and complexity of the developed software is high. Predicting the quality of software in early phases helps to reduce testing resources. Various statistical and machine learning techniques are used for prediction of the quality of the software. In this paper, six machine learning models have been used for software quality prediction on five open source software. Varieties of metrics have been evaluated for the software including C & K, Henderson & Sellers, McCabe etc. Results show that Random Forest and Bagging produce good results while Naïve Bayes is least preferable for prediction.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of King Saud University - Computer and Information Sciences - Volume 30, Issue 1, January 2018, Pages 2-17
نویسندگان
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