Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
8-1-2019 12:00 AM
End Date
11-1-2019 12:00 AM
Description
Automated test case generation is one of the main challenges in testing mobile applications. This challenge becomes more complicated when the application being tested supports motion-based events. In this paper, we propose a novel, hidden Markov model (HMM)-based approach to automatically generate movement-based gestures in mobile applications. A HMM classifier is used to generate movements, which mimic a user’s behaviour in interacting with the application’s User Interface (UI). We evaluate the proposed technique on three different case studies; the evaluation indicates that the technique not only generates realistic test cases, but also achieves better code coverage when compared to randomly generated test cases
Automated Testing of Motion-based Events in Mobile Applications
Grand Wailea, Hawaii
Automated test case generation is one of the main challenges in testing mobile applications. This challenge becomes more complicated when the application being tested supports motion-based events. In this paper, we propose a novel, hidden Markov model (HMM)-based approach to automatically generate movement-based gestures in mobile applications. A HMM classifier is used to generate movements, which mimic a user’s behaviour in interacting with the application’s User Interface (UI). We evaluate the proposed technique on three different case studies; the evaluation indicates that the technique not only generates realistic test cases, but also achieves better code coverage when compared to randomly generated test cases
https://aisel.aisnet.org/hicss-52/st/mobile_app_development/6