Jam Jam Satyanarayana
In this paper, we deal with the software bugs where large software company spent lot many of their cost in the same. The step of fixing the bug is called as bug triage where we correctly assign a developer to a new bug. Here, we address the problem of data reduction for bug triage. The problem of data reduction deal with how to reduce the scale and improve the quality. Hence, we combine instance selection with feature selection both simultaneously to reduce bug dimension and word dimension. We also extract the historical bug data set and predictive model to build new data set. This work provides leveraging techniques on data processing for high quality bug data in the software development.
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