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Verification, Model Checking, and Abstract Interpretation: 25th International Conference, VMCAI 2024, London, United Kingdom, January 1516, 2024, Proceedings, Part II 1st ed. 2024 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 340 pages, height x width: 235x155 mm, weight: 551 g, 71 Illustrations, color; 37 Illustrations, black and white; XVIII, 340 p. 108 illus., 71 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14500
  • Izdošanas datums: 03-Jan-2024
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031505204
  • ISBN-13: 9783031505201
  • Mīkstie vāki
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  • Formāts: Paperback / softback, 340 pages, height x width: 235x155 mm, weight: 551 g, 71 Illustrations, color; 37 Illustrations, black and white; XVIII, 340 p. 108 illus., 71 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 14500
  • Izdošanas datums: 03-Jan-2024
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031505204
  • ISBN-13: 9783031505201
The two-volume set LNCS 14499 and 14500 constitutes the proceedings of the 25th International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2024, which took place in London, Ontario, Canada, in January 2024. 

The 30 full papers presented in the proceedings were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows:
Part I: Abstract interpretation; infinite-state systems; model checking and synthesis; SAT, SMT, and automated reasoning; 
Part II: Concurrency; neural networks; probabilistic and quantum programs; program and system verification; runtime verification; security and privacy; 

Concurrency.- Petrification: Software Model Checking for Programs with
Dynamic Thread Management.- A Fully Verified Persistency Library.- A
Navigation Logic for Recursive Programs with Dynamic Thread Creation.- Neural
Networks.- Taming Reachability Analysis of DNN-Controlled Systems
via Abstraction-Based Training.- Verification of Neural Networks' Local
Differential Classification Privacy.- AGNES: Abstraction-guided Framework for
Deep Neural Network Security.- Probabilistic and Quantum Programs Guaranteed
inference for probabilistic programs: a parallelisable, small-step
operational approach.- Local Reasoning about Probabilistic Behaviour for
Classical-Quantum Programs.- Program and System Verification.- Deductive
Verification of Parameterized Embedded Systems modeled in
SystemC.- Automatically Enforcing Rust Trait Properties.- Borrowable
Fractional Ownership Types for Verification.- Runtime
Verification.- TP-DejaVu: Combining Operational and Declarative Runtime
Verification.- Synthesizing Efficiently Monitorable Formulas in Metric
Temporal Logic.- Security and Privacy.- Automatic and Incremental Repair for
Speculative Information Leaks.- Sound Abstract Nonexploitability Analysis.