When representation learning meets software analysis

In recent years, deep learning is increasingly prevalent in the field of Software Engineering (SE). Especially, representation learning, which can learn vectors from the syntactic and semantics of the code, offers much convenience and promotion for the downstream tasks such as code search and vulnerability detection. In this work, we introduce our two applications of leveraging representation learning for software analysis, including defect prediction and vulnerability detection.