Mobile games play an increasingly important role in our daily life. The quality of mobile games can substantially affect the user experience and game revenue. Different from traditional mobile games, the mini-games provided by our partner, Tencent, are embedded in the mobile app WeChat, so users do not need to install specific game apps and can directly play the games in the app. Due to the convenient installation, WeChat has attracted large numbers of developers to design and publish on the mini-game platform in the app. Until now, the platform has more than one hundred thousand published mini-games. Manually testing all the mini-games requires enormous effort and is impractical. There exist automated game testing methods; however, they are difficult to be applied for testing mini-games for the following reasons: 1) Effective game testing heavily relies on prior knowledge about game operations and extraction of GUI widget trees. However, this knowledge is specific and not always applicable when testing a large number of mini-games with complex game engines (e.g., Unity). 2) The highly diverse GUI widget design of mini-games deviates significantly from that of mobile apps. Such issue prevents the existing image-based GUI widget detection techniques from effectively detecting widgets in mini-games.

To address the aforementioned issues, we propose a unified framework for black-box mini-game testing named iExplorer. iExplorer involves a mixed GUI widget detection approach incorporating both deep learning-based object detection and edge aggregation-based segmentation for detecting GUI widgets in mini-games. A category-aware testing strategy is then proposed for testing mini-games, with different categories of widgets (e.g., sliding and clicking widgets) considered. iExplorer has been deployed in WeChatfor more than six months. In the past 30 days, iExplorer has tested large-scale mini-games (i.e., 76,000) and successfully found 22,144 real bugs.