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API misuses are prevalent and extremely harmful. Despite various techniques have been proposed for API-misuse detection, it is not even clear how different types of API misuses distribute and whether existing techniques have covered all major types of API misuses. Therefore, in this paper, we conduct the first large-scale empirical study on API misuses based on 528,546 historical bug-fixing commits from GitHub (from 2011 to 2018). By leveraging a state-of-the-art fine-grained AST differencing tool, GumTree, we extract more than one million bug-fixing edit operations, 51.7% of which are API misuses. We further systematically classify API misuses into nine different categories according to the edit operations and context. We also extract various frequent API-misuse patterns based on the categories and corresponding operations, which can be complementary to existing API-misuse detection tools. Our study reveals …