Computer Aided Verification 36th International Conference, CAV 2024, Montreal, QC, Canada, July 24–27, 2024, Proceedings, Part I
This open access 3-volume set constitutes the proceedings of the 36th International Conference on Computer-Aided Verification, CAV 2024, which took place in Montreal, Canada, during July 24–27, 2024. The primary focus of CAV is to extend the frontiers of verification techniques by expanding to new d...
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| Format: | E-Book |
| Sprache: | Englisch |
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Springer Nature
2024
Springer |
| Ausgabe: | 1 |
| Schriftenreihe: | Lecture Notes in Computer Science |
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| ISBN: | 9783031656279, 303165627X, 3031656261, 9783031656262 |
| Online-Zugang: | Volltext |
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Inhaltsangabe:
- 6.1 Methodology -- 6.2 Prevalence of SDBMs -- 6.3 Applications to Translation Validation -- 7 Related Work -- 8 Conclusion -- References -- The Top-Down Solver Verified: Building Confidence in Static Analyzers -- 1 Introduction -- 2 Preliminaries -- 3 The Plain Top-Down Solver -- 4 The Top-Down Solver -- 5 Related Work -- 6 Conclusion -- References -- End-to-End Mechanized Proof of a JIT-Accelerated eBPF Virtual Machine for IoT -- 1 Introduction -- 1.1 Challenges -- 1.2 Contributions -- 2 Preliminaries -- 3 A Workflow for End-to-End Refinement -- 3.1 Methodology -- 3.2 Application to a rBPF Virtual Machine -- 4 Symbolic CompCert ARM Interpreter -- 5 A Verified Just-In-Time Compiler for rBPF -- 5.1 JIT Design -- 5.2 JIT Correctness -- 5.3 JIT Vertical Refinement -- 6 HAVM: A Hybrid Interpreter for rBPF -- 7 Evaluation: Case Study of RIOT's Femto-Containers -- 8 Lessons Learned -- 9 Related Works -- 10 Conclusion -- References -- A Framework for Debugging Automated Program Verification Proofs via Proof Actions -- 1 Introduction -- 2 Proof Debugging Considered Painful -- 2.1 Background on Automated Program Verification in Verus -- 2.2 Examples of Proof Debugging -- 2.3 Automated Proof Debugging with Proof Actions -- 2.4 Challenges with Automatic Code Transformation -- 3 ProofPlumber: An Extensible Proof Action Framework -- 3.1 ProofPlumber's API Design -- 3.2 ProofPlumber's Implementation -- 4 Evaluation -- 4.1 RQ1: Are proof actions expressive enough? -- 4.2 RQ2: Does ProofPlumber make it easy to write proof actions? -- 4.3 RQ3: Can proof actions reduce the verifier's TCB? -- 5 Limitations -- 6 Related Work and Conclusion -- References -- Verification Algorithms for Automated Separation Logic Verifiers -- 1 Introduction -- 2 Verification Algorithms -- 2.1 Viper Verification Language -- 2.2 Design Dimensions -- 2.3 Algorithms -- 3 Evaluation
- 4 Derivative-Based Construction for Nested Formulae -- 5 Simple Rewriting Rules -- 6 Disjunction Pruning -- 7 Quantifier Instantiation -- 7.1 Quantifier Instantiation Based on Formula Monotonicity -- 7.2 Range-Based Quantifier Instantiation -- 7.3 Modulo Linearization -- 8 A Comprehensive Example of Our Optimizations -- 9 Experimental Evaluation -- 10 Related Work -- References -- Distributed SMT Solving Based on Dynamic Variable-Level Partitioning -- 1 Introduction -- 2 Preliminaries -- 2.1 Definitions and Notations -- 2.2 Parallel SMT Solving with Partitioning -- 2.3 Interval Constraint Propagation -- 3 Dynamic Parallel Framework Based on Arithmetic Partitioning -- 3.1 The Framework -- 3.2 Partition Tree Maintenance and UNSAT Propagation -- 3.3 Terminate on Demand -- 3.4 A Running Example -- 4 Variable-Level Partitioning for Arithmetic Theories -- 4.1 Preprocessing -- 4.2 The Partitioning Algorithm -- 4.3 BICP in Arithmetic Partitioning -- 5 Evaluation -- 5.1 Evaluation Preliminaries -- 5.2 Comparison to Sequential Solving -- 5.3 Comparison to State-of-the-art Partitioning Strategies -- 5.4 Improvement on Pure-Conjunction Formulas -- 6 Conclusion and Future Work -- References -- Quantified Linear Arithmetic Satisfiability via Fine-Grained Strategy Improvement -- 1 Introduction -- 2 Fine-Grained Game Semantics for LRA Satisfiability -- 2.1 Linear Rational Arithmetic -- 2.2 Fine-Grained Game Semantics -- 3 Fine-Grained Strategy Skeletons -- 4 Fine-Grained Strategy Improvement -- 5 Computing Counter-Strategies -- 5.1 Term Selection -- 6 Synthesizing Fine-Grained Strategies -- 7 Experimental Evaluation -- 8 Discussion and Related Works -- References -- From Clauses to Klauses* -- 1 Introduction -- 2 Background -- 2.1 Cardinality Constraints -- 2.2 Conflict-Driven Clause Learning and Proofs of Unsatisfiability
- 1 Introduction -- 2 SMLP Architecture -- 3 Symbolic Representation of Models and Constraints -- 4 Symbolic Representation of the ML Model Exploration -- 5 Problem Specification in SMLP -- 6 SMLP Exploration Modes of ML Models -- 6.1 Stable Parameter Synthesis -- 6.2 Verifying Assertions on a Model -- 6.3 Querying Conditions on the Model -- 6.4 Stable Optimized Synthesis -- 6.5 Design of Experiments -- 6.6 Root Cause Analysis -- 6.7 Model Refinement Loop -- 7 Implementation -- 8 Industrial Case Studies -- 9 Future Work -- References -- Avoiding the Shoals - A New Approach to Liveness Checking -- 1 Introduction -- 2 Preliminaries -- 2.1 Boolean Satisfiability -- 2.2 Boolean Transition Systems -- 2.3 Invariant Checking -- 2.4 Liveness Checking -- 3 Liveness Checking with rlive -- 3.1 Overview -- 3.2 Algorithm -- 3.3 Optimizations -- 3.4 Correctness Proof -- 4 Related Work -- 5 Evaluation -- 5.1 Experimental Setup -- 5.2 Experimental Results -- 6 Conclusions -- References -- Toward Liveness Proofs at Scale -- 1 Introduction -- 2 Background and Related Work -- 2.1 Liveness-to-Safety with Rankings -- 2.2 Dynamic Liveness-to-Safety Construction -- 3 Relational Rankings -- 3.1 The Relational Reactivity Rule -- 3.2 Chaining Liveness Lemmas -- 3.3 Stable Schedulers -- 3.4 Lexicographic Rankings -- 4 Case Study: The Apple Generic Memory Subsystem Model -- 4.1 Liveness Proof with Lemmas -- 4.2 Lemma-Free Proof of Liveness -- 5 Conclusions and Future Work -- A Soundness proofs -- References -- Software Verification -- Strided Difference Bound Matrices -- 1 Introduction and Motivation -- 2 DBMs, SDBMs, and HSDBMs -- 3 Satisfiability -- 3.1 GCD-Tightening Constraints -- 3.2 Satisfiability for HSDBMs in O(n4) Time -- 3.3 Satisfiability for SDBMs in O(n m Dlcm) Time -- 4 HSDBM Normalization -- 5 Operations for Abstract Interpretation -- 6 Empirical Study
- Intro -- Preface -- Organization -- Invited Talks -- How to Solve Math Problems Without Talent -- Bridging Formal Mathematics and Software Verification -- The Art of SMT Solving -- Contents - Part I -- Contents - Part II -- Contents - Part III -- Decision Procedures -- Split Gröbner Bases for Satisfiability Modulo Finite Fields -- 1 Introduction -- 1.1 Related Work -- 2 Background -- 3 Motivating Example -- 3.1 Verifying the Determinism of Num2Bits -- 3.2 The Challenge of Bit-Splitting -- 3.3 Cooperative Reasoning: A Path Forward -- 4 Approach -- 4.1 Split Gröbner bases -- 4.2 Abstract Procedure: Split -- 4.3 Concrete Procedure: BitSplit -- 5 Experiments -- 5.1 Benchmarks -- 5.2 Comparison to Prior Solvers -- 5.3 Comparison to Variants -- 6 Application -- 6.1 Background on Verifiable Field-Blasting -- 6.2 A New Strategy for Verifying Operator Rules -- 7 Conclusion -- A Additional Background -- B Computing Bitsum Usage in Real World Projects -- C Proof of Theorem 1 -- D Proof of Theorems 2 and 3 -- E Proof of Lemma 1 -- F The Seq Benchmark Family -- G Proof of Theorem 4 -- References -- Arithmetic Solving in Z3 -- 1 Introduction -- 2 Design Goals and Implementation Choices -- 3 Linear Real Arithmetic -- 3.1 Linear Solving -- 3.2 Finding Equal Variables - Cheaply -- 3.3 Bounds Propagation -- 4 Integer Linear Arithmetic -- 4.1 Patching -- 4.2 Cubes -- 4.3 GCD Consistency -- 4.4 Branching -- 4.5 Cuts -- 5 Non-linear Arithmetic -- 5.1 Patch Monomials -- 5.2 Bounds Propagation -- 5.3 Adding Bounds -- 5.4 Gröbner reduction -- 5.5 Incremental Linearization -- 5.6 NLSat -- 6 Shared Equalities -- 7 Evaluation -- 8 Summary and Discussion -- References -- Algebraic Reasoning Meets Automata in Solving Linear Integer Arithmetic -- 1 Introduction -- 2 Preliminaries -- 3 Classical Automata-Based Decision Procedure for LIA
- 3.1 Implementations
- 3 At-Least-K Conjunctive Normal Form (KNF) -- 4 Cardinality Constraint Extraction and Analysis -- 4.1 Extraction -- 4.2 Analysis with BDDs -- 4.3 PySAT Encodings Experimental Evaluation -- 5 Cardinality Conflict-Driven Clause Learning -- 5.1 Implementation Details -- 5.2 Inprocessing Techniques -- 6 Proof Checking -- 6.1 Satisfying Assignments -- 6.2 Clausal Proofs -- 6.3 Starting with KNF Input -- 7 Experimental Evaluation -- 7.1 SAT Competition Benchmarks -- 7.2 Magic Squares and Max Squares -- 8 Conclusion and Future Work -- References -- CaDiCaL 2.0 -- 1 Introduction -- 2 Architecture -- 3 External Propagator -- 4 Proofs -- 5 Tracer Interface -- 6 Constraints and Flipping -- 7 Interpolation -- 8 Testing and Debugging -- 9 Experiments -- 10 Conclusion -- References -- Formally Certified Approximate Model Counting -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Approximate Model Counting -- 3.2 Formalization in Isabelle/HOL -- 4 Approximate Model Counting in Isabelle/HOL -- 4.1 Abstract Specification and Probabilistic Analysis -- 4.2 Concretization to a Certificate Checker -- 4.3 Extending ApproxMC to ApproxMCCert -- 4.4 CNF-XOR Unsatisfiability Checking -- 5 Experimental Evaluation -- 6 Conclusion and Future Work -- References -- Scalable Bit-Blasting with Abstractions -- 1 Introduction -- 2 Preliminaries -- 3 Abstraction-Refinement Framework -- 4 Refinement Schemes -- 4.1 Hand-Crafted Lemmas -- 4.2 Lemma Scoring Scheme -- 4.3 Synthesizing Lemmas via Abduction -- 4.4 Lemma Verification -- 5 Integration -- 6 Evaluation -- 7 Conclusion -- References -- Hardware Model Checking -- The MoXI Model Exchange Tool Suite -- 1 Overview -- 2 Intermediate Language -- 3 Tool Suite -- 3.1 Translators -- 3.2 Utilities -- 4 Tool Suite Validation -- 5 Benchmarks -- 6 Conclusion and Future Work -- References -- SMLP: Symbolic Machine Learning Prover