Enhanced Feature Selection Algorithm for Effective Bug Triage Software
Keywords:
Bug, Bug Triage, Kruskal Method, Feature Selection, Instance Selection.Abstract
For building up any software application or item it is important to discover the bug in the item while building up the item. At each period of testing the bug report is created, more often than not is squandered for fixing the bug. Software businesses squander 45 percent of expense in fixing the bug. For fixing the bug one of the basic techniques is bug triage. Bug triage is a process for fixing the bugs whose primary item is to suitably assign a designer to a novel bug for further dealing with. At first manual work is accomplished for each time producing the bug report. After that content categorization techniques are useful to conduct, ordinary bug triage. The current framework faces the issue of data reduction in the fixing of bugs consequently. Consequently, there is a need of a technique which diminishes the range additionally improves the brilliance of bug data. Conventional framework utilized CH strategy for highlight choice which does not give precise outcomes. Along these lines, in this paper proposed the technique for highlight choice by utilizing the Kruskal strategy. By joining the case accumulation and the element gathering calculations to simultaneously diminish the data scale likewise upgrade the precision of the bug reports in the bug triage. By utilizing the Kruskal strategy to expel uproarious words in a data set. This technique can improve the accuracy misfortune by case accumulation.
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