Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/67382
Title: ATOM : Automatic maintenance of GUI test scripts for evolving mobile applications
Authors: Li, X
Chang, N
Wang, Y
Huang, H
Pei, Y 
Wang, L
Li, X
Issue Date: 2017
Publisher: IEEE
Source: Proceedings - 10th IEEE International Conference on Software Testing, Verification and Validation, ICST 2017, 7927972, p. 161-171 How to cite?
Abstract: The importance of regression testing in assuring the integrity of a program after changes is well recognized. One major obstacle in practicing regression testing is in maintaining tests that become obsolete due to evolved program behavior or specification. For mobile apps, the problem of maintaining obsolete GUI test scripts for regression testing is even more pressing. Mobile apps rely heavily on the correct functioning of their GUIs to compete on the market and provide good user experiences. But on the one hand, GUI tests break easily when changes happen to the GUI; On the other hand, mobile app developers often need to fight for a tight feedback loop and are left with limited time fur test maintenance.In this paper, we propose a novel approach, called ATOM, to automatically maintain GUI test scripts of mobile apps for regression testing. ATOM uses an event sequence model to abstract possible event sequences on a GUI and a delta ESM to abstract the changes made to the GUI. Given both models as input, ATOM automatically updates the test scripts written for a base version app to reflect the changes. In an experiment with 22 versions from 11 production Android apps, ATOM updated all the test scripts affected by the version change; the updated scripts achieve over 80% of the coverage by the original scripts on the base version app; all except one set of updated scripts preserve over 60% of the actions in the original test scripts.
Description: 10th IEEE International Conference on Software Testing, Verification and Validation, ICSTW 2017, Tokyo, Japan, 13-17 March 2017
URI: http://hdl.handle.net/10397/67382
ISBN: 978-1-5090-6031-3
ISSN: 2381-2834
DOI: 10.1109/ICST.2017.22
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