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Found 5 papers, 1 papers with code
CNNSAT: Fast, Accurate Boolean Satisfiability using Convolutional Neural Networks
Boolean satisfiability (SAT) is one of the most well-known NP-complete problems and has been extensively studied.
Infrared: A Meta Bug Detector
The recent breakthroughs in deep learning methods have sparked a wave of interest in learning-based bug detectors.
WheaCha: A Method for Explaining the Predictions of Models of Code
Attribution methods have emerged as a popular approach to interpreting model predictions based on the relevance of input features.
Learning Semantic Program Embeddings with Graph Interval Neural Network
We have also created a neural bug detector based on GINN to catch null pointer deference bugs in Java code.
Learning a Static Bug Finder from Data
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.
