文章基本信息

标题：Analysing Pattern for Chromium Bug Area Classification
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作者：Trasha Gupta ; Monika Gupta
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：3
页码：3478-3482
出版社：TechScience Publications
摘要：Software maintenance in software engineering is the modification of a software product after delivery to correct faults, to improve performance or other attributes. The purpose is to preserve the value of software over the time. The users report the bugs in the issue tracking system. Bug report contains many fields like title, description, version, OS, area etc. The quality of bug report affects the repair time. It is noticed that users often assign incorrect or don’t assign the area of bug which lead to bug reassignment and hence delay. Document categorization (based on text) with its diversified application has been widely studied by data mining, machine learning, and information retrieval communities. In this work we analyse the linguistic patterns to classify the bug into most three common areas: UI, web-kit and internals. The data set will be categorized using different classifiers viz. Naive Bayes, Support Vector Machine and Neural Networks etc
关键词：Text classification; area prediction