1 citations · 4 across the 13 of their papers we have counts for
13 papers
Partial Contracts Suffice: Sound, LLM-Inferred Regression Verification
Yiannis Charalambous, Rafael Menezes, Youcheng Sun +1
Software evolves continuously, yet ensuring that a patch preserves intended behavior without re-verifying an entire codebase remains difficult. Regression verification addresses th…
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…
GPT, But Backwards: Exactly Inverting Language Model Outputs
Adrians Skapars, Edoardo Manino, Youcheng Sun +1
Recent work shows that distinct inputs produce distinct hidden representations in LLMs, so the input can in principle be recovered from them. Yet, no existing method can reliably d…
Neural Network Verification is a Programming Language Challenge
Lucas C. Cordeiro, Matthew L. Daggitt, Julien Girard-Satabin +8
Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while pr…
Was it Slander? Towards Exact Inversion of Generative Language Models
Adrians Skapars, Edoardo Manino, Youcheng Sun +1
Training large language models (LLMs) requires a substantial investment of time and money. To get a good return on investment, the developers spend considerable effort ensuring tha…
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…
ESBMC v7.6: Enhanced Model Checking of C++ Programs with Clang AST
Xianzhiyu Li, Kunjian Song, Mikhail R. Gadelha +4
This paper presents Efficient SMT-Based Context-Bounded Model Checker (ESBMC) v7.6, an extended version based on previous work on ESBMC v7.3 by K. Song et al. The v7.3 introduced a…
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…
FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning
Kaled M. Alshmrany, Mohannad Aldughaim, Chenfeng Wei +3
We present FuSeBMC-AI, a test generation tool grounded in machine learning techniques. FuSeBMC-AI extracts various features from the program and employs support vector machine and…
Generative transformations and patterns in LLM-native approaches for software verification and falsification
Víctor A. Braberman, Flavia Bonomo-Braberman, Yiannis Charalambous +3
The emergence of prompting as the dominant paradigm for leveraging Large Language Models (LLMs) has led to a proliferation of LLM-native software, where application behavior arises…
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,…