4 citations · 8 across the 12 of their papers we have counts for
6 papers · 1 filter
Floating-Point Neural Network Verification at the Software Level
Edoardo Manino, Bruno Farias, Rafael Sá Menezes +2
The behaviour of neural network components must be proven correct before deployment in safety-critical systems. Unfortunately, existing neural network verification techniques canno…
Interval Analysis in Industrial-Scale BMC Software Verifiers: A Case Study
Rafael Sá Menezes, Edoardo Manino, Fedor Shmarov +3
Bounded Model Checking (BMC) is a widely used software verification technique. Despite its successes, the technique has several limiting factors, from state-space explosion to lack…
Verifying components of Arm(R) Confidential Computing Architecture with ESBMC
Tong Wu, Shale Xiong, Edoardo Manino +2
Realm Management Monitor (RMM) is an essential firmware component within the recent Arm Confidential Computing Architecture (Arm CCA). Previous work applies formal techniques to ve…
Automated Repair of AI Code with Large Language Models and Formal Verification
Yiannis Charalambous, Edoardo Manino, Lucas C. Cordeiro
The next generation of AI systems requires strong safety guarantees. This report looks at the software implementation of neural networks and related memory safety properties, inclu…
ESBMC v7.4: Harnessing the Power of Intervals
Rafael Menezes, Mohannad Aldughaim, Bruno Farias +9
ESBMC implements many state-of-the-art techniques for model checking. We report on new and improved features that allow us to obtain verification results for previously unsupported…
NeuroCodeBench: a plain C neural network benchmark for software verification
Edoardo Manino, Rafael Sá Menezes, Fedor Shmarov +1
Safety-critical systems with neural network components require strong guarantees. While existing neural network verification techniques have shown great progress towards this goal,…