173 citations · 397 across the 28 of their papers we have counts for
5 papers · 1 filter
A New Era in Software Security: Towards Self-Healing Software via Large Language Models and Formal Verification
Norbert Tihanyi, Ridhi Jain, Yiannis Charalambous +3
This paper introduces an innovative approach that combines Large Language Models (LLMs) with Formal Verification strategies for automatic software vulnerability repair. Initially,…
An Overview of Structural Coverage Metrics for Testing Neural Networks
Muhammad Usman, Youcheng Sun, Divya Gopinath +3
Deep neural network (DNN) models, including those used in safety-critical domains, need to be thoroughly tested to ensure that they can reliably perform well in different scenarios…
Tutorials on Testing Neural Networks
Nicolas Berthier, Youcheng Sun, Wei Huang +3
Deep learning achieves remarkable performance on pattern recognition, but can be vulnerable to defects of some important properties such as robustness and security. This tutorial i…
RobOT: Robustness-Oriented Testing for Deep Learning Systems
Jingyi Wang, Jialuo Chen, Youcheng Sun +4
Recently, there has been a significant growth of interest in applying software engineering techniques for the quality assurance of deep learning (DL) systems. One popular direction…
Functional Requirements-Based Automated Testing for Avionics
Youcheng Sun, Martin Brain, Daniel Kroening +7
We propose and demonstrate a method for the reduction of testing effort in safety-critical software development using DO-178 guidance. We achieve this through the application of Bo…