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Enhanced Feature Selection Algorithm for Effective Bug Triage Software

  • Jayashri C. Gholap
  • N. P. Karlekar
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 10)

Abstract

For developing any software application or product it is necessary to find the bug in the product while developing the product. At every phase of testing the bug report is generated, most of the time is wasted for fixing the bug. Software industries waste 45% of cost in fixing the bug. For fixing the bug one of the essential techniques is bug triage. Bug triage is a process for fixing the bugs whose main object is to appropriately allocate a developer to a novel bug for further handling. Initially manual work is needed for every time generating the bug report. After that content categorization methods are functional to behavior regular bug triage. The existing system faces the problem of data reduction in the fixing of bugs automatically. Therefore, there is a need of method which decreases the range also improves the excellence of bug information. Traditional system used CH method for feature selection which is not give accurate result. Therefore, in this paper proposed the method of feature selection by using the Kruskal method. By combining the instance collection and the feature collection algorithms to concurrently decrease the data scale also enhance accuracy of the bug reports in the bug triage. By using Kruskal method remove noisy words in a data set. This method can improve the correctness loss by instance collection.

Keywords

Bug Bug triage Kruskal method Feature selection Instance selection 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Sinhgad Institute of TechnologyLonavalaIndia

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