Survey on General Classification Techniques for Effective Bug Triage

International Journal of Computer Science and Engineering
© 2015 by SSRG - IJCSE Journal
Volume 2 Issue 11
Year of Publication : 2015
Authors : Nitu Bhardwaj, A.S Bhattacharya

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How to Cite?

Nitu Bhardwaj, A.S Bhattacharya, "Survey on General Classification Techniques for Effective Bug Triage," SSRG International Journal of Computer Science and Engineering , vol. 2,  no. 11, pp. 6-10, 2015. Crossref, https://doi.org/10.14445/23488387/IJCSE-V2I11P102

Abstract:

Data mining is the process of extraction of hidden and useful information from huge data. It is also called knowledge discovery process from data. Bug tracking systems are made to manage bug reports, which are collected from various sources. These bug reports are needed to be labeled as security bug reports or non-security bug reports. Data mining uses to apply mining algorithm to extract information which is stored in bug tracking systems. Classification is a task of data mining. Data mining can be applied to any kind of data as long as the data are meaningful for a target application. The most basic forms of data for mining applications are database data, data warehouse data and transactional data. This paper presents a survey on several classification techniques for effective bug triage which are generally used for data mining such as naïve bayes, decision tree, K- nearest neighbor, Rule based, neural network etc.

Keywords:

Bug report, classification, naïve bayes, decisiontree, K-nearest neighbor, Rule based, neural network.

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