Real-Time Error Detection In Digital Games Based on the YOLO V10 Model

Digital games are programs that aim to engage users, often by visually interacting with the game; to evoke a sense of enjoyment. As with any software, digital games can contain bugs. These bugs can cause the games to not function as intended, either visually or logically. Therefore, bug detection in digital games is an area that game developers worldwide are focusing on and investing resources in. Examples of these resources include the time spent on identifying bugs and the employment of game testers by the companies to find these bugs. This study aims to perform automatic and effective bug detection in digital games using a real-time object recognition, classification, and image processing model called YOLO. The latest version of the YOLO model, YOLO v10, was used in this study. To facilitate the detection of bugs, a three-dimensional experimental environment was created using the Unity game engine, and some visual and logical bugs commonly found in games were introduced into this environment. The images of these bugs were used to create a dataset; that was then used as training and test data for the YOLO v 10 model; to enable real-time detection of game bugs. The aim of this study is to achieve effective, automated; detection of digital game bugs in real time using the YOLO v10 model.