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Mastering the knowledge about the bug-prone functions (i.e., sensitive functions) is important to detect bugs. Some automated techniques have been proposed to identify the sensitive functions in large software systems, based on machine learning or natural language processing. However, the existing statistics-based techniques are not directly applicable to a special kind of sensitive functions, i.e., the rare sensitive functions, which have very few invocations even in large systems. Unfortunately, the rare ones can also introduce bugs. Therefore, how to effectively identify such functions is a problem deserving attention.
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Huang et al. (2024) studied this question.
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