03734nam 2200493 450 991076027870332120240113030858.0981-9975-84-010.1007/978-981-99-7584-6(MiAaPQ)EBC30876552(Au-PeEL)EBL30876552(DE-He213)978-981-99-7584-6(EXLCZ)992880478810004120240113h20242023 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierFormal Methods and Software Engineering 24th International Conference on Formal Engineering Methods, ICFEM 2023, Brisbane, QLD, Australia, November 21-24, 2023, Proceedings /Yi Li and Sofiène Tahar, editorsFirst edition.Singapore :Springer,[2024]©20231 online resource (319 pages)Lecture Notes in Computer Science Series ;Volume 14308Print version: Li, Yi Formal Methods and Software Engineering Singapore : Springer Singapore Pte. Limited,c2023 9789819975839 Includes bibliographical references and index.Invited Talk: Verifying Compiler Optimisations -- Regular Papers: An Idealist’s Approach for Smart Contract Correctness -- Active Inference of EFSMs Without Reset -- Learning Mealy Machines with Local Timers -- Compositional Vulnerability Detection with Insecurity Separation Logic -- Dynamic Extrapolation in Extended Timed Automata -- Formalizing Robustness against Character-level Perturbations for Neural Network Language Models -- Trace models of concurrent valuation algebras -- Branch and Bound for Sigmoid-like Neural Network Verification -- Certifying Sequential Consistency of Machine Learning Accelerators -- Guided Integration of Formal Verification in Assurance Cases -- Validation-Driven Development -- Incremental Property Directed Reachability -- Proving Local Invariants in ASTDs -- Doctoral Symposium Papers: Formal Verification of the Burn-to-Claim Blockchain Interoperable Protocol -- Early and systematic validation of formal models -- Verifying Neural Networks by Approximating Convex Hulls -- Eager to Stop: Efficient Falsification of Deep Neural Networks -- A Runtime Verification Framework For Cyber-physical Systems Based On Data Analytics And LTL Formula Learning -- Unified Verification of Neural Networks’ Robustness and Privacy in Computer Vision -- IoT Software Vulnerability Detection Techniques through Large Language Model -- Vulnerability Detection via Typestate-Guided Code Representation Learning.This book constitutes the proceedings of the 24th International Conference on Formal Methods and Software Engineering, ICFEM 2023, held in Brisbane, QLD, Australia, during November 21–24, 2023. The 13 full papers presented together with 8 doctoral symposium papers in this volume were carefully reviewed and selected from 34 submissions, the volume also contains one invited paper. The conference focuses on applying formal methods to practical applications and presents papers for research in all areas related to formal engineering methods.Lecture notes in computer science ;Volume 14308.Formal methods (Computer science)CongressesSoftware engineeringCongressesFormal methods (Computer science)Software engineering004.0151Li YiTahar SofièneMiAaPQMiAaPQMiAaPQBOOK9910760278703321Formal Methods and Software Engineering771999UNINA