Automatic bug classification using machine learning

A machine learning engine can be used to identify inconsistencies and errors in a plurality of bug reports and to glean new information from the bug reports. Bug data associated with a large number of bug reports from different bug categories may be processed and used by a machine learning model of the machine learning engine. The machine learning engine can extract bug attributes from the bug data of a first bug. The machine learning engine can then compare the attributes of the first bug to a machine learning model created using a plurality of second bug reports. Based on then similarity between the first bug report and the second bug reports, the machine learning engine can apply, or correct, various attributes of the first bug report. The machine learning model may be updated over time by the machine learning engine as data correlations evolve.