  The code clone detection method based on semantic similarity has important
value in software engineering tasks (e.g., software evolution, software reuse).
Traditional code clone detection technologies pay more attention to the
similarity of code at the syntax level, and less attention to the semantic
similarity of the code. As a result, candidate codes similar in semantics are
ignored. To address this issue, we propose a code clone detection method based
on semantic similarity. By treating code as a series of interdependent events
that occur continuously, we design a model namely EDAM to encode code semantic
information based on event embedding and event dependency. The EDAM model uses
the event embedding method to model the execution characteristics of program
statements and the data dependence information between all statements. In this
way, we can embed the program semantic information into a vector and use the
vector to detect codes similar in semantics. Experimental results show that the
performance of our EDAM model is superior to state of-the-art open source
models for code clone detection.
