## Computer Aided Verification: 33rd International Conference, CAV 2021, Virtual Event, July 20–23, 2021, Proceedings, Part IThis open access two-volume set LNCS 12759 and 12760 constitutes the refereed proceedings of the 33rd International Conference on Computer Aided Verification, CAV 2021, held virtually in July 2021. The 63 full papers presented together with 16 tool papers and 5 invited papers were carefully reviewed and selected from 290 submissions. The papers were organized in the following topical sections: Part I: invited papers; AI verification; concurrency and blockchain; hybrid and cyber-physical systems; security; and synthesis. Part II: complexity and termination; decision procedures and solvers; hardware and model checking; logical foundations; and software verification. This is an open access book. |

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### Contents

3 | |

26 | |

46 | |

Programmable Program Synthesis | 84 |

Techniques Challenges Opportunities | 110 |

AI Verification | 135 |

A Framework for Deep Neural Network Verification | 137 |

Robustness Verification of Quantum Classifiers | 151 |

Modeling and Formal Analysis of Virtually Synchronous CPSs in AADL | 491 |

Computing Bottom SCCs Symbolically Using Transition Guided Reduction | 505 |

Implicit SemiAlgebraic Abstraction for Polynomial Dynamical Systems | 529 |

Synthesis of Timing Parameters Beyond Decidability | 552 |

Formally Verified Switching Logic for Recoverability of Aircraft Controller | 566 |

Boosting Scenario Verification Using Symmetry Abstractions | 580 |

Effective Hybrid System Falsification Using Monte Carlo Tree Search Guided by QBRobustness | 595 |

Fast ZoneBased Algorithms for Reachability in Pushdown Timed Automata | 619 |

A BDDBased Quantitative Analysis Framework for Binarized Neural Networks | 175 |

Automated Safety Verification of Programs Invoking Neural Networks | 201 |

Scalable Polyhedral Verification of Recurrent Neural Networks | 225 |

Verification of Neural Network Controllers Using Taylor Model Preconditioning | 249 |

Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability | 263 |

PenalizedRelaxation Greedy Neural Network Verifier | 287 |

Concurrency and Blockchain | 301 |

Integrating FullScale ISA Semantics and Axiomatic Concurrency Models | 302 |

Summing up Smart Transitions | 317 |

Stateless Model Checking Under a ReadsValueFrom Equivalence | 341 |

Modular Specification and Verification of Go Programs | 367 |

DelayBounded Scheduling Without Delay | 380 |

Checking DataRace Freedom of GPU Kernels Compositionally | 403 |

A Model Checker for Weak Memory Models | 427 |

Hybrid and CyberPhysical Systems | 441 |

Synthesizing Invariant Barrier Certificates via DifferenceofConvex Programming | 443 |

An Iterative Scheme of Safe Reinforcement Learning for Nonlinear Systems via Barrier Certificate Generation | 467 |

Security | 643 |

Verified Cryptographic Code for Everybody | 644 |

Not All Bugs Are Created Equal But Robust Reachability Can Tell the Difference | 669 |

A Temporal Logic for Asynchronous Hyperproperties | 694 |

Retrofitting Program Verifiers to Check Information Flow Security | 718 |

ConstraintBased Relational Verification | 742 |

Predeployment Security Assessment for Cloud Services Through Semantic Reasoning | 767 |

Synthesis | 781 |

Synthesis with Asymptotic Resource Bounds | 783 |

Program Sketching by Automatically Generating Mocks from Tests | 808 |

CounterexampleGuided Partial Bounding for Recursive Function Synthesis | 832 |

A Tool for Inductive Synthesis of Probabilistic Programs | 856 |

Adapting Behaviors via Reactive Synthesis | 870 |

CausalityBased Game Solving | 894 |

918 | |

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Computer Aided Verification: 33rd International Conference, CAV 2021 ... Alexandra Silva,K. Rustan M. Leino No preview available - 2021 |

### Common terms and phrases

abstract algorithm allows analysis applied approach automatically barrier benchmarks bound calls certificate changes checking Commons complex compute concurrent condition consider constraints construction controller defined Definition denote describe efficient encoding evaluation example execution existing expressions formal formula function given goal hybrid images implementation included initial input instance interpretation invariant language layer learning linear LNCS logic loop memory method neural networks Note obtain operations optimization output path performance possible predicate present problem proof properties prove reach reachability reasoning recursive reduce relation represent requires respectively robustness rule safe safety satisfies Sect semantics solution solver solving specification Springer step strategy structure symbolic synthesis techniques Theorem thread tion tool trace transition University variables verification winning