文章基本信息

标题：SQA by Defect prediction: An SVM based In-Appendage Software Development Log Analysis
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作者：N.Rajasekhar Reddy ; M.VinayaBabu
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2018
卷号：9
期号：6
页码：140-146
出版社：TechScience Publications
摘要：The present paper proposes a Machine learning technique for defect forecasting and handling for SQA called appendage log training and analysis, can be referred as ALTA. The proposed defect forecasting of in-appendage software development logs works is to deal the forecasted defects accurately and spontaneously while developing the software. The present proposed mechanism helps in minimizing the difficulty of SQA. The overall study is conducted on evaluating the proposed model which indicates the defect forecasting in-appendage software development log training and analysis is significant growth to lessen the complexity of Software Quality Assessment.
关键词：Hybrid software development method; conventional software development methods; agile software development methods; Software Engineering