A Technique to Combine Feature Selection with Instance Selection for Effective Bug Triage

Software organizations spend more than 45 percent of expense in managing Software bugs. An unavoidable step of altering bugs is bug triage, which plans to accurately allot a developer to another bug. To reduce the time cost in manual work, text classification methods are used for automatic bug triage. In this undertaking, we address the issue of data reduction for bug triage, i. e. , how to diminish the scale and improve the nature of bug data. We consolidate instance selection with feature selection to simultaneously decrease information scale on the bug dimension and the word dimension. This paper gives a way to deal with utilizing methods on data processing to form reduced and high-quality bug data in software development and maintenance and also improve the results of data reduction in bug triage.