92 citations · 252 across the 14 of their papers we have counts for
4 papers · 1 filter
On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations
Md Rafiqul Islam Rabin, Nghi D. Q. Bui, Ke Wang +3
With the prevalence of publicly available source code repositories to train deep neural network models, neural program models can do well in source code analysis tasks such as pred…
Learning Semantic Program Embeddings with Graph Interval Neural Network
Yu Wang, Fengjuan Gao, Linzhang Wang +1
Learning distributed representations of source code has been a challenging task for machine learning models. Earlier works treated programs as text so that natural language methods…
Learning Blended, Precise Semantic Program Embeddings
Ke Wang, Zhendong Su
Learning neural program embeddings is key to utilizing deep neural networks in program languages research --- precise and efficient program representations enable the application o…
Learning a Static Bug Finder from Data
Yu Wang, Fengjuan Gao, Linzhang Wang +1
We present an alternative approach to creating static bug finders. Instead of relying on human expertise, we utilize deep neural networks to train static analyzers directly from da…