Abstract:
Code clone detection plays an important role in software maintenance and evolution. There are
many new applications emerging that rely on clones detected across software systems, and hence
to address this, many code clone detection tools are being developed. However only a few of them
target semantic clones. With deep learning taking a new turn today, extensive work has started
to leverage these models to detect clones. These models use lexical information and syntactic
structures like the abstract syntax trees to detect the clones, however, these methods do not
take into account the available structural and semantic information that the codes offer and
this limits the capabilities of such methods. Using Program Dependence Graphs and attention
based learning, we want to fully leverage the structured syntactic and semantic information and
develop a tool which can be used to detect the clone which might differ syntactically but yield
the same semantics.
