  Mobile applications (apps) often suffer from failure nowadays. Developers
usually pay more attention to the failure that is perceived by users and
compromises the user experience. Existing approaches focus on mining large
volume logs to detect failure, however, to our best knowledge, there is no
approach focusing on detecting whether users have actually perceived failure,
which directly influence the user experience. In this paper, we propose a novel
approach to detecting user-perceived failure in mobile apps. By leveraging the
frontend user traces, our approach first builds an app page model, and applies
an unsupervised detection algorithm to detect whether a user has perceived
failure. Our insight behind the algorithm is that when user-perceived failure
occurs on an app page, the users will backtrack and revisit the certain page to
retry. Preliminary evaluation results show that our approach can achieve good
detection performance on a dataset collected from real world users.
