Can we rely on smartphone applications?
This addresses reliability issues for smartphone users and developers, but is incremental as it adapts existing statistical models to a new domain.
The study tackled the problem of assessing smartphone application reliability by testing traditional software reliability models and found they were inadequate, while demonstrating that Weibull and Gamma distribution models could better fit failure data to predict reliability.
Smartphones are becoming necessary tools in the daily lives of mil-lions of users who rely on these devices and their applications. There are thou-sands of applications for smartphone devices such as the iPhone, Blackberry, and Android, thus their reliability has become paramount for their users. This work aims to answer two related questions: (1) Can we assess the reliability of mobile applications by using the traditional reliability models? (2) Can we model adequately the failure data collected from many users? Firstly, it has been proved that the three most used software reliability models have fallen short of the mark when applied to smartphone applications; their failures were traced back to specific features of mobile applications. Secondly, it has been demonstrated that the Weibull and Gamma distribution models can adequately fit the observed failure data, thus providing better means to predict the reliability of smartphone applications.