Computer Aided Verification 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21–24, 2020, Proceedings, Part I
The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.* The 43 full papers presented together with 18 tool papers and 4 case studies, were care...
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Springer Nature
2020
Springer International Publishing AG |
| Vydání: | 1 |
| Edice: | Lecture Notes in Computer Science; Theoretical Computer Science and General Issues |
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| ISBN: | 9783030532871, 3030532879 |
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| Abstract | The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.* The 43 full papers presented together with 18 tool papers and 4 case studies, were carefully reviewed and selected from 240 submissions. The papers were organized in the following topical sections: Part I: AI verification; blockchain and Security; Concurrency; hardware verification and decision procedures; and hybrid and dynamic systems. Part II: model checking; software verification; stochastic systems; and synthesis. *The conference was held virtually due to the COVID-19 pandemic. |
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| AbstractList | The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.* The 43 full papers presented together with 18 tool papers and 4 case studies, were carefully reviewed and selected from 240 submissions. The papers were organized in the following topical sections: Part I: AI verification; blockchain and Security; Concurrency; hardware verification and decision procedures; and hybrid and dynamic systems. Part II: model checking; software verification; stochastic systems; and synthesis. *The conference was held virtually due to the COVID-19 pandemic. |
| Author | Wang, Chao Lahiri, Shuvendu K |
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| Editor | Wang, Chao Lahiri, Shuvendu K |
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| SubjectTerms | architecture verification and validation Artificial intelligence Computer Engineering and Networks Computer hardware Computer networking & communications Computer networking and communications computer networks computer programming Computer programming / software engineering Computer science computer systems Computer Systems Organization and Communication Networks Computing and Information Technology data security Database Management System distributed computer systems embedded systems formal logic Information Systems and Communication Service linguistics Mathematical theory of computation model checking network protocols Open Access parallel processing systems signal processing software architecture software design Software Engineering software quality Theory of Computation verification and validation |
| Subtitle | 32nd International Conference, CAV 2020, Los Angeles, CA, USA, July 21–24, 2020, Proceedings, Part I |
| TableOfContents | Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- I AI Verification -- NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems -- 1 Introduction -- 2 Overview and Features -- 3 Set Representations and Reachability Algorithms -- 3.1 Polyhedron ch1tran2019parallel -- 3.2 Star Set ch1tran2019fm,ch1tran2019emsoft (code) -- 3.3 Zonotope ch1singh2018fast (code) -- 3.4 Abstract Domain ch1singh2019abstract -- 3.5 ImageStar Set ch1tran2020cav (code) -- 4 Evaluation -- 4.1 Safety Verification of ACAS Xu Networks -- 4.2 Safety Verification of Adaptive Cruise Control System -- 5 Related Work -- 6 Conclusions -- References -- Verification of Deep Convolutional Neural Networks Using ImageStars -- 1 Introduction -- 2 Problem Formulation -- 3 ImageStar -- 4 Reachability of CNN Using ImageStars -- 4.1 Reachability of a Convolutional Layer -- 4.2 Reachability of an Average Pooling Layer -- 4.3 Reachability of a Fully Connected Layer -- 4.4 Reachability of a Batch Normalization Layer -- 4.5 Reachability of a Max Pooling Layer -- 4.6 Reachability of a ReLU Layer -- 4.7 Reachabilty Algorithm and Parallelization -- 5 Evaluation -- 5.1 Robustness Verification of MNIST Classification Networks -- 5.2 Robustness Verification of VGG16 and VGG19 -- 5.3 Exact Analysis vs. Approximate Analysis -- 6 Discussion -- 7 Conclusion -- References -- An Abstraction-Based Framework for Neural Network Verification -- 1 Introduction -- 2 Background -- 2.1 Neural Networks -- 2.2 Neural Network Verification -- 3 Network Abstraction and Refinement -- 3.1 Abstraction -- 3.2 Refinement -- 4 A CEGAR-Based Approach -- 4.1 Generating an Initial Abstraction -- 4.2 Performing the Refinement Step -- 5 Implementation and Evaluation -- 6 Related Work -- 7 Conclusion -- References Improved Geometric Path Enumeration for Verifying ReLU Neural Networks -- 1 Introduction -- 2 Background -- 2.1 Neural Networks and Verification -- 2.2 Basic Geometric Path Enumeration Algorithm -- 2.3 Spatial Data Structures -- 2.4 ACAS Xu Benchmarks -- 3 Improvements -- 3.1 Local Search Type (DFS vs BFS) -- 3.2 Bounds for Splitting -- 3.3 Fewer LPs with Concrete Simulations -- 3.4 Zonotope Prefilter -- 3.5 Eager Bounds Computation -- 3.6 Zonotope Contraction -- 4 Evaluation with Other Tools -- 5 Related Work -- 6 Conclusions -- A Box Bounds Algorithm for Box-Halfspace Intersection -- B Parallelization -- C Full Optimization Data -- D Full Tool Comparison Data -- References -- Systematic Generation of Diverse Benchmarks for DNN Verification -- 1 Motivation -- 2 Background and Related Wok -- 3 Identifying Factors that Influence Verifier Performance -- 3.1 Potential Factors -- 3.2 Exploratory Factor Study -- 4 The GDVB Approach -- 4.1 Factor Diverse Benchmarks -- 4.2 From Factor Covering Arrays to Verification Problems -- 4.3 Generating Benchmarks -- 4.4 An Instantiation of GDVB -- 5 GDVB in Use -- 5.1 Setup -- 5.2 Comparing Verifiers Across a Range of Challenges -- 5.3 GDVB and Benchmark Requirements R1-R3 -- 6 Conclusion -- References -- Formal Analysis and Redesign of a Neural Network-Based Aircraft Taxiing System with VerifAI -- 1 Introduction -- 2 Extensions of VerifAI -- 3 TaxiNet Case Study -- 3.1 Experimental Setup -- 3.2 Falsification -- 3.3 Error Analysis and Debugging -- 3.4 Retraining -- 4 Conclusion -- References -- I Blockchain and Security -- The Move Prover -- 1 Introduction -- 2 Background: The Move Language -- 3 Tool Overview -- 4 Boogie Model -- 5 Specifications -- 6 Evaluation -- 7 Related Work -- 8 Conclusion -- References -- End-to-End Formal Verification of Ethereum 2.0 Deposit Smart Contract -- 1 Introduction 4.1 Yield Invariants and Linear Interfaces -- 4.2 Linearity -- 4.3 Safety -- 4.4 Refinement -- 5 Implementation -- 6 Conclusions -- References -- Parameterized Verification of Systems with Global Synchronization and Guards -- 1 Introduction -- 2 System Model: Global Synchronization Protocols -- 2.1 Global Synchronization Without Guards -- 2.2 Global Synchronization with Guards -- 3 Parameterized Verification for GSPs Without Guards -- 3.1 Compatibility and Effective Computability of Predecessors -- 3.2 Decidability for Unguarded GSPs -- 4 Parameterized Verification for GSPs with Guards -- 4.1 Guard-Compatibility and Well-Behaved Processes -- 4.2 Decidability for Well-Behaved Guarded Processes -- 5 Cutoffs for GSPs -- 5.1 Definition and Basic Observations -- 5.2 Conditions for Small Cutoffs -- 6 Applications and Evaluation -- 7 Related Work -- 8 Conclusion -- References -- HAMPA: Solver-Aided Recency-Aware Replication -- 1 Introduction -- 2 Recency-Aware Relational Object Language -- 3 Coordination Conditions -- 4 Replicated System Semantics -- 5 Staleness Bound Inference and Optimization -- 6 The Power and the Protocol of Recency-Aware Objects -- 7 Experimental Results -- 8 Related Work -- 9 Conclusion -- References -- Root Causing Linearizability Violations -- 1 Introduction -- 2 Overview -- 3 Preliminaries -- 4 Linearizability Violations and Their Root Causes -- 4.1 Repair Oracle Approximation -- 4.2 Generalization to Multiple Traces -- 5 Conflict-Serializability Repairs -- 5.1 Repairs and Conflict Cycles -- 5.2 A Simple Algorithm -- 5.3 A Sound Optimization -- 6 Repair List Generation -- 6.1 Optimal Repairs Enumeration Algorithm -- 6.2 Ranking Optimal Repairs -- 7 Experimental Evaluation -- 8 Related Work -- References -- Symbolic Partial-Order Execution for Testing Multi-Threaded Programs -- 1 Introduction -- 2 Overview 1.1 Our Refinement-Based Verification Approach -- 2 Formal Verification of the Deposit Contract -- 2.1 Incremental Merkle Tree Algorithm -- 2.2 Bytecode Verification of the Deposit Contract -- 3 Findings and Lessons Learned -- 3.1 Maximum Number of Deposits -- 3.2 ABI Standard Conformance of get_deposit_count Function -- 3.3 Checking Well-Formedness of Calldata -- 3.4 Liveness -- 3.5 Discussion -- 4 Related Work -- References -- Stratified Abstraction of Access Control Policies -- 1 Introduction -- 2 Overview -- 2.1 Approach -- 2.2 Solution: Computing Findings via Stratified Abstraction -- 3 Algorithm -- 3.1 Policies and Findings -- 3.2 Properties -- 3.3 Algorithm -- 4 Implementation and Evaluation -- 5 Related Work -- References -- Synthesis of Super-Optimized Smart Contracts Using Max-SMT -- 1 Introduction -- 2 Overview: Optimal Bytecode as a Synthesis Problem -- 2.1 Extracting Stack Functional Specifications from EVM Bytecode -- 2.2 The Synthesis Problem -- 2.3 Characteristics of Our SMT Encoding of the Synthesis Problem -- 2.4 Optimal Synthesis Using Max-SMT -- 3 Stack Functional Specification from EVM Bytecode -- 4 Optimal Synthesis Using Max-SMT -- 4.1 Abstracting Uninterpreted Functions -- 4.2 Modeling the Stack -- 4.3 Encoding of Instructions -- 4.4 From Models to EVM Blocks -- 4.5 Optimization Using Max-SMT -- 5 Experimental Evaluation -- 5.1 Comparison with ebso (setup I) -- 5.2 Analysis of the Most Called Contracts with Gas Savings (setup Ii) -- 5.3 Comparison of SMT Solvers in Precision and Time -- 6 Related Work -- 7 Conclusions and Future Work -- References -- Verification of Quantitative Hyperproperties Using Trace Enumeration Relations -- 1 Introduction -- 2 Motivating Example -- 2.1 Preliminaries -- 2.2 Motivating Example: Zero-Knowledge Hats -- 2.3 Solution Outline -- 3 Overview of Quantitative Hyperproperties 2.1 Sequential Executions 3.1 Quantitative Hyperproperties -- 3.2 Applications of QHPs in Security Specification -- 4 Trace Enumerations -- 4.1 Trace Enumeration Relations -- 5 Model Counting -- 5.1 Model Counting via SMT Solving -- 5.2 Model Counting in the Motivating Example -- 6 Experimental Results and Discussion -- 6.1 Methodology -- 6.2 Overview of Results -- 6.3 Deniability of Path ORAM -- 7 Related Work -- 8 Conclusion -- References -- Validation of Abstract Side-Channel Models for Computer Architectures -- 1 Introduction -- 2 Background -- 2.1 Observational Models -- 2.2 The Evaluation Platform: Raspberry Pi 3 -- 2.3 Different Attacker and Observational Models -- 2.4 Binary Intermediate Representation -- 3 Program Generation -- 4 Synthesis of Weakest Relation -- 5 Test-Case Generation -- 6 Implementation -- 7 Results -- 7.1 Direct-Mapped Cache Observational Model -- 7.2 Partitioned Cache Observational Model -- 7.3 Multi-way Cache Observational Model -- 7.4 Problems in Model Implementations -- 8 Related Work -- 9 Concluding Remarks -- References -- I Concurrency -- Semantics, Specification, and Bounded Verification of Concurrent Libraries in Replicated Systems -- 1 Introduction -- 2 Illustrative Example -- 3 Semantics and Specifications -- 3.1 Language Semantics -- 3.2 Abstract Execution Semantics -- 3.3 Replicated Store Semantics -- 3.4 Correctness Specification -- 4 Bounded Verification -- 4.1 Vocabulary -- 4.2 Implementation Constraints -- 4.3 Abstract Execution Constraints -- 4.4 Replicated Store Constraints -- 4.5 Specification Constraints -- 5 Experimental Evaluation -- 6 Related Work and Conclusion -- References -- Refinement for Structured Concurrent Programs -- 1 Introduction -- 1.1 Related Work -- 2 Overview -- 2.1 Yield Invariants -- 2.2 Refining Atomic Actions -- 2.3 Linear Interfaces -- 3 RefPL: Syntax and Semantics -- 4 Abstracting RefPL Programs |
| Title | Computer Aided Verification |
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