Titlebook: Integrated Formal Methods; 18th International C Paula Herber,Anton Wijs Conference proceedings 2024 The Editor(s) (if applicable) and The A

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Lifting the?Reasoning Level in?Generic Weak Memory Verificationssertion language, we provide a number of novel . for directly reasoning on the level of program constructs. We prove soundness of our proof rules and exemplify them on the write-to-read causality (WRC) litmus test. A comparison to the axiom-based low-level proof reveals a significant reduction in the number of required proof steps.

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SMT: Something You Must Try help of SMT solvers, and - in case of satisfiability - (iii) decodes their solutions back to solutions of the original real-world problem..In this extended abstract we give some insights into the working mechanisms of SMT solving, discuss a few areas of application, and present a novel application from the domain of simulation.

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Refinement and?Separation: Modular Verification of?Wandering Treesearch trees, trees in RAM that are partially loaded from snapshots on flash, where only modified parts are incrementally saved, and the efficient representation of trees as pointer structures. This paper proposes a modular solution that allows verifying each aspect separately. The solution has been mechanized in the theorem prover KIV.

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Performance Fuzzing?with Reinforcement-Learning and?Well-Defined Constraints for?the?B Methodethod, which differences exist to the original implementation for the SMT-LIB standard, and how we ensure well-definedness of the randomly generated benchmarks. Our experiments successfully uncovered performance issues in specific backends and even external tooling, providing valuable insights into areas which required improvement.

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Conference proceedings 2024herlands.??. .The 16 full papers presented together with 2 short papers were carefully reviewed and selected from 51 submissions.?The conference focuses on?all aspects of the design of integrated techniques, including language design, verification and validation, automated tool support, and the use

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st matches the experimental data from free viewing of natural images. Because saccade programming models depend on the foveated point, we took into account the spatially variant retinal resolution. We showed that the predicted eye fixations were more effective when this retinal resolution was combin