3 papers
stat.ML2020
Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models
Alexis Cooper, Xin Zhou, Scott Heidbrink +1
Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems. In this work, we demonstrate that even bet…
cs.LG2020
Multimodal Deep Learning for Flaw Detection in Software Programs
Scott Heidbrink, Kathryn N. Rodhouse, Daniel M. Dunlavy
We explore the use of multiple deep learning models for detecting flaws in software programs. Current, standard approaches for flaw detection rely on a single representation of a s…
cs.CR2019
A Review of Machine Learning Applications in Fuzzing
Gary J Saavedra, Kathryn N Rodhouse, Daniel M Dunlavy +1
Fuzzing has played an important role in improving software development and testing over the course of several decades. Recent research in fuzzing has focused on applications of mac…