Survey on Bug Triage with Software Data Reduction Techniques
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 125 | Views: 418

Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 12, December 2015 | Popularity: 6.9 / 10


     

Survey on Bug Triage with Software Data Reduction Techniques

Jayashri Gholap, N. P. Karlekar


Abstract: Bug triage is an essential step in the process of bug fixing. Bug triage is the process of fixing bug whose main objective is to correctly allocate a developer to a new bug further handling. Many software companies spend their most of cost in dealing with these bugs. To decrease the time cost in manual work and to enhance the working of automatic bug triage, two techniques are applied namely text classification and binary classification. In literature various papers address the problem of data reduction for bug triage, i. e. , how to reduce the scale and improve the quality of bug data. By combining the instance selection and the feature selection algorithms to simultaneously reduce the data scale and enhance the accuracy of the bug reports in the bug triage. This survey focused on various data reduction technique for bug triage. As per literature, need to develop a effective model for doing data reduction on bug data set which will reduce the scale of the data as well as increase the quality of the data. , by reducing the time and cost.


Keywords: Bug triage, data reduction, Instance selection, Feature selection, Data Mining, Mining software repositories


Edition: Volume 4 Issue 12, December 2015


Pages: 690 - 693


DOI: https://www.doi.org/10.21275/NOV152065


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Jayashri Gholap, N. P. Karlekar, "Survey on Bug Triage with Software Data Reduction Techniques", International Journal of Science and Research (IJSR), Volume 4 Issue 12, December 2015, pp. 690-693, https://www.ijsr.net/getabstract.php?paperid=NOV152065, DOI: https://www.doi.org/10.21275/NOV152065

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