(Updated submission 11/20/2020) MISIM: A Novel Code Similarity System

no code implementations • 28 Sep 2020 • Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Niranjan Hasabnis, Paul Petersen, Timothy G Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich

First, MISIM uses a novel context-aware semantic structure (CASS), which is designed to aid in lifting semantic meaning from code syntax.

MISIM: A Neural Code Semantics Similarity System Using the Context-Aware Semantics Structure

no code implementations • 5 Jun 2020 • Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Nesime Tatbul, Jesmin Jahan Tithi, Niranjan Hasabnis, Paul Petersen, Timothy Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich

Code semantics similarity can be used for many tasks such as code recommendation, automated software defect correction, and clone detection.

Clone Detection

Context-Aware Parse Trees

no code implementations • 24 Mar 2020 • Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich

The simplified parse tree (SPT) presented in Aroma, a state-of-the-art code recommendation system, is a tree-structured representation used to infer code semantics by capturing program \emph{structure} rather than program \emph{syntax}.