2 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…