CNNSAT: Fast, Accurate Boolean Satisfiability using Convolutional Neural Networks

no code implementations • ICLR 2019 • Yu Wang, Fengjuan Gao, Amin Alipour, Linzhang Wang, Xuandong Li, Zhendong Su

Boolean satisfiability (SAT) is one of the most well-known NP-complete problems and has been extensively studied.

Learning Semantic Program Embeddings with Graph Interval Neural Network

no code implementations • 18 May 2020 • Yu Wang, Fengjuan Gao, Linzhang Wang, Ke Wang

We have also created a neural bug detector based on GINN to catch null pointer deference bugs in Java code.

Method name prediction Variable misuse

Learning a Static Bug Finder from Data

1 code implementation • 12 Jul 2019 • Yu Wang, Fengjuan Gao, Linzhang Wang, Ke Wang

In a cross-project prediction task, three neural bug detectors we instantiate from NeurSA are effective in catching null pointer dereference, array index out of bound and class cast bugs in unseen code.