Context In the field of Software issue report, the process involving the correct classification of potential new bugs is often time consuming and expensive. One of the main causes of this phenomenon is bound to the fact that this process is human based, and as consequence this usually leads to frequent mis-classifications. Since errors lead to waste of time and resources they have to be efficiently reduced to the minimum. Moreover, reducing the time for bug triaging would reduce the cost of the entire bug removal process. Goal The aim of this thesis is building a tool that will automatically classify the bug and assign it to the correct class.