
Effective PreSilicon Verification of Processor Cores by Breaking the Bounds of Symbolic Quick Error Detection
We present a novel approach to presilicon verification of processor des...
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lazybvtoint at the SMT Competition 2020
lazybvtoint is a new prototype SMTsolver, that will participate in the ...
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Automated Design Space Exploration of CGRA Processing Element Architectures using Frequent Subgraph Analysis
The architecture of a coarsegrained reconfigurable array (CGRA) process...
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Politeness and Stable Infiniteness: Stronger Together
We make two contributions to the study of polite combination in satisfia...
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DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers
We introduce DeepCert, a toolsupported method for verifying the robustn...
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CounterexampleGuided Prophecy for Model Checking Modulo the Theory of Arrays
We develop a framework for model checking infinitestate systems by auto...
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An SMTBased Approach for Verifying Binarized Neural Networks
Deep learning has emerged as an effective approach for creating modern s...
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Global Optimization of Objective Functions Represented by ReLU Networks
Neural networks (NN) learn complex nonconvex functions, making them des...
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SmtSwitch: a solveragnostic C++ API for SMT Solving
This extended abstract describes work in progress on SmtSwitch, an open...
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fault: A Python Embedded DomainSpecific Language For Metaprogramming Portable Hardware Verification Components
While hardware generators have drastically improved design productivity,...
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A Theoretical Framework for Symbolic Quick Error Detection
Symbolic quick error detection (SQED) is a formal presilicon verificati...
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Parallelization Techniques for Verifying Neural Networks
Inspired by recent successes with parallel optimization techniques for s...
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Politeness for the Theory of Algebraic Datatypes
Algebraic datatypes, and among them lists and trees, have attracted a lo...
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Verifying Recurrent Neural Networks using Invariant Inference
Deep neural networks are revolutionizing the way complex systems are dev...
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G2SAT: Learning to Generate SAT Formulas
The Boolean Satisfiability (SAT) problem is the canonical NPcomplete pr...
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Simplifying Neural Networks with the Marabou Verification Engine
Deep neural network (DNN) verification is an emerging field, with divers...
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Verifying Bitvector Invertibility Conditions in Coq (Extended Abstract)
This work is a part of an ongoing effort to prove the correctness of inv...
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CVC4SY for SyGuSCOMP 2019
CVC4Sy is a syntaxguided synthesis (SyGuS) solver based on bounded term...
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DRATbased BitVector Proofs in CVC4
Many stateoftheart Satisfiability Modulo Theories (SMT) solvers for t...
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Towards BitWidthIndependent Proofs in SMT Solvers
Many SMT solvers implement efficient SATbased procedures for solving fi...
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Algorithms for Verifying Deep Neural Networks
Deep neural networks are widely used for nonlinear function approximatio...
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Symbolic QED Presilicon Verification for Automotive Microcontroller Cores: Industrial Case Study
We present an industrial case study that demonstrates the practicality a...
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Processor Hardware Security Vulnerabilities and their Detection by Unique Program Execution Checking
Recent discovery of security attacks in advanced processors, known as Sp...
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CVC4 at the SMT Competition 2018
This paper is a description of the CVC4 SMT solver as entered into the 2...
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On Solving Quantified BitVectors using Invertibility Conditions
We present a novel approach for solving quantified bitvector formulas i...
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EMME: a formal tool for ECMAScript Memory Model Evaluation
Nearly all webbased interfaces are written in JavaScript. Given its pre...
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Toward Scalable Verification for SafetyCritical Deep Networks
The increasing use of deep neural networks for safetycritical applicati...
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Logic Bug Detection and Localization Using Symbolic Quick Error Detection
We present Symbolic Quick Error Detection (Symbolic QED), a structured a...
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DeepSafe: A Datadriven Approach for Checking Adversarial Robustness in Neural Networks
Deep neural networks have become widely used, obtaining remarkable resul...
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GroundTruth Adversarial Examples
The ability to deploy neural networks in realworld, safetycritical sys...
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Towards Proving the Adversarial Robustness of Deep Neural Networks
Autonomous vehicles are highly complex systems, required to function rel...
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Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Deep neural networks have emerged as a widely used and effective means f...
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Clark Barrett
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