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Horn-ICE learning for synthesizing invariants and contracts
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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A Practical and Complete Approach to Predicate Refinement
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Boogie: A Modular Reusable Verifier for Object-Oriented Programs
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Houdini, an Annotation Assistant for ESC/Java
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ICE: A Robust Framework for Learning Invariants
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From Invariant Checking to Invariant Inference Using Randomized Search
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SMACK: Decoupling Source Language Details from Verifier Implementations
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The SeaHorn Verification Framework
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Property-Directed Inference of Universal Invariants or Proving Their Absence
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IC3 - Flipping the E in ICE
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Invariant Synthesis for Incomplete Verification Engines
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ICE-Based Refinement Type Discovery for Higher-Order Functional Programs
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Interpolation and SAT-Based Model Checking
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Linear Invariant Generation Using Non-linear Constraint Solving
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Z3: An Efficient SMT Solver
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InvGen: An Efficient Invariant Generator
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SAT-Based Model Checking without Unrolling
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Interpolants as Classifiers
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Generalized Property Directed Reachability
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Ultimate Automizer with SMTInterpol
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A Data Driven Approach for Algebraic Loop Invariants
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Verification as Learning Geometric Concepts
inferredcites →https://doi.org/10.1007/978-3-642-38856-9_8openalex-snapshot
On Solving Universally Quantified Horn Clauses
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Learning Universally Quantified Invariants of Linear Data Structures
inferredcites →https://doi.org/10.1007/978-3-642-39799-8_61openalex-snapshot
Solving Existentially Quantified Horn Clauses
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Relational Thread-Modular Static Value Analysis by Abstract Interpretation
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Software Verification with Validation of Results
inferredcites →https://doi.org/10.1007/bf01211617openalex-snapshot
The rely-guarantee method for verifying shared variable concurrent programs
inferredcites →https://doi.org/10.1016/0743-1066(84)90014-1openalex-snapshot
Linear-time algorithms for testing the satisfiability of propositional horn formulae
inferredcites →https://doi.org/10.1145/1375581.1375616openalex-snapshot
Program analysis as constraint solving
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Program analysis as constraint solving
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Synthesizing software verifiers from proof rules
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Synthesizing software verifiers from proof rules
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Automatic predicate abstraction of C programs
inferredcites →https://doi.org/10.1145/2509136.2509511openalex-snapshot
Inductive invariant generation via abductive inference
inferredcites →https://doi.org/10.1145/2837614.2837664openalex-snapshot
Learning invariants using decision trees and implication counterexamples
inferredcites →https://doi.org/10.1145/2908080.2908099openalex-snapshot
Data-driven precondition inference with learned features
inferredcites →https://doi.org/10.1145/2908080.2908125openalex-snapshot
Automatically learning shape specifications
inferredcites →https://doi.org/10.1145/2914770.2837664openalex-snapshot
Learning invariants using decision trees and implication counterexamples
inferredcites →https://doi.org/10.1145/2970276.2970305openalex-snapshot
Inferring annotations for device drivers from verification histories
inferredcites →https://doi.org/10.1145/2980983.2908125openalex-snapshot
Automatically learning shape specifications
inferredcites →https://doi.org/10.1145/337180.337240openalex-snapshot
Quickly detecting relevant program invariants
inferredcites →https://doi.org/10.1145/360051.360224openalex-snapshot
Verifying properties of parallel programs
inferredcites →https://doi.org/10.1145/378795.378846openalex-snapshot
Automatic predicate abstraction of C programs
inferredcites →https://doi.org/10.1145/381694.378846openalex-snapshot
Automatic predicate abstraction of C programs
inferredcites →https://doi.org/10.1145/69575.69577openalex-snapshot
Tentative steps toward a development method for interfering programs
inferredcites →https://doi.org/10.23919/fmcad.2017.8102247openalex-snapshot
Sampling invariants from frequency distributions
inferredcites →https://doi.org/10.48550/arxiv.1302.2273openalex-snapshot
Learning Universally Quantified Invariants of Linear Data Structures
inferredcites →https://doi.org/10.5555/2337223.2337304openalex-snapshot
Using dynamic analysis to discover polynomial and array invariants
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Programming Languages and Systems
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Maximal Quantified Precondition Synthesis for Linear Array Loops
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ConstraintFlow: A Declarative DSL for Easy Development of DNN Certifiers
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Discovering Likely Invariants for Distributed Systems Through Runtime Monitoring and Learning
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Data-Driven Verification of Procedural Programs with Integer Arrays
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