  Bug triaging is a process to decide what to do with newly coming bug reports.
In this paper, we have mined association rules for the prediction of bug
assignee of a newly reported bug using different bug attributes, namely,
severity, priority, component and operating system. To deal with the problem of
large data sets, we have taken subsets of data set by dividing the large data
set using K-means clustering algorithm. We have used an Apriori algorithm in
MATLAB to generate association rules. We have extracted the association rules
for top 5 assignees in each cluster.The proposed method has been empirically
validated on 14696 bug reports of Mozilla open source software project, namely,
Seamonkey, Firefox and Bugzilla. The proposed method provides an improvement
over the existing techniques for bug assignment problem.
