Abstract
With the increasing popularity of mobile applications, a light-weighted bug tracking systems has been widely needed. While the high release frequency of the mobile applications requires a rapid bug tracking system for the software maintenance, the needs for users’ feedback can be easily accessed and manipulated for both common users and developers, which motivates us to develop a mobile service for bug tracking, namely Mubug, by combining the natural language processing technique and machine learning technique. Project managers can easily configure and setup bug tracking service without any installation on Mubug. Reporters can submit bug reports with texts, voices or images using their mobile devices. Bug reports can thus be processed and assigned to developers automatically. In this paper, we present the architecture of Mubug and some implememtation details.
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