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To ensure app compatibility and smoothness of user experience across diversedevices and platforms, developers have to perform cross-device, cross-platformtesting of their apps, which is laborious. There comes a recently increasingtrend of using a record and replay approach to facilitate the testing process.However, the graphic user interface (GUI) of an app running on differentdevices and platforms differs dramatically. This complicates the record andreplay process as the presence, appearance and layout of the GUI widgets in therecording phase and replaying phase can be inconsistent. Existing techniquesresort to instrumenting into the underlying system to obtain the app metadatafor widget identification and matching between various devices. But suchintrusive practices are limited by the accessibility and accuracy of themetadata on different platforms. On the other hand, several recent worksattempt to derive the GUI information by analyzing the GUI image. Nevertheless,their performance is curbed by the applied preliminary visual approaches andthe failure to consider the divergence of the same GUI displayed on differentdevices. To address the challenge, we propose a non-intrusive cross-device andcross-platform system NiCro. NiCro utilizes the state-of-the-art GUI widgetdetector to detect widgets from GUI images and then analyses a set ofcomprehensive information to match the widgets across diverse devices. At thesystem level, NiCro can interact with a virtual device farm and a robotic armsystem to perform cross-device, cross-platform testing non-intrusively. Wefirst evaluated NiCro by comparing its multi-modal widget and GUI matchingapproach with 4 commonly used matching techniques. Then, we further examinedits overall performance on 8 various devices, using it to record and replay 107test cases of 28 popular apps and the home page to show its effectiveness.

NiCro: Purely Vision-based, Non-intrusive Cross-Device and Cross-Platform GUI Testing