Verification, Model Checking, and Abstract Interpretation [electronic resource] : 23rd International Conference, VMCAI 2022, Philadelphia, PA, USA, January 16-18, 2022, Proceedings / edited by Bernd Finkbeiner, Thomas Wies.
Contributor(s): Finkbeiner, Bernd [editor.]
| Wies, Thomas [editor.] | SpringerLink (Online service).
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BookSeries: Theoretical Computer Science and General Issues: 13182Publisher: Cham : Springer International Publishing : Imprint: Springer, 2022Edition: 1st ed. 2022.Description: X, 520 p. 154 illus., 80 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030945831.Subject(s): Computer science | Mathematical logic | Artificial intelligence | Computer networks | Theory of Computation | Mathematical Logic and Foundations | Artificial Intelligence | Computer Communication NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 004.0151 Online resources: Click here to access online
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Springer Nature eBookSummary: This book constitutes the proceedings of the 23rd International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2022, which took place in Philadelphia, PA, USA, in January 2022. The 22 papers presented in this volume were carefully reviewed from 48 submissions. VMCAI provides a forum for researchers working on verification, model checking, and abstract interpretation and facilitates interaction, cross-fertilization, and advancement of hybrid methods that combine these and related areas.
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This book constitutes the proceedings of the 23rd International Conference on Verification, Model Checking, and Abstract Interpretation, VMCAI 2022, which took place in Philadelphia, PA, USA, in January 2022. The 22 papers presented in this volume were carefully reviewed from 48 submissions. VMCAI provides a forum for researchers working on verification, model checking, and abstract interpretation and facilitates interaction, cross-fertilization, and advancement of hybrid methods that combine these and related areas.
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