Verification of Data-Aware Processes via Satisfiability Modulo Theories

Gianola, Alessandro.

Verification of Data-Aware Processes via Satisfiability Modulo Theories [electronic resource] / by Alessandro Gianola. - 1st ed. 2023. - XXVIII, 317 p. 28 illus. online resource. - Lecture Notes in Business Information Processing, 470 1865-1356 ; . - Lecture Notes in Business Information Processing, 470 .

Introduction -- 1.1 Overview -- 1.1.1 Finite-State Model Checking -- 1.1.2 Verification of Data-Aware Processes -- 1.1.3 Infinite-state Model Checking: from Parameterized Systems to SMT Verification -- 1.1.4 Main Goal of the Book -- 1.2 Related Literature -- 1.2.1 Formal Models for Data-Aware (Business) Processes -- 1.2.2 Verification of Data-Aware Processes -- 1.2.3 Model Checking for Infinite-State Systems using SMT-based Techniques -- 1.3 Contributions of the Book -- 1.3.1 Contributions of the First Part -- 1.3.2 Contributions of the Second Part -- 1.3.3 Contributions of the Third Part -- Part I Foundations of SMT-based Safety Verification of Artifact Systems -- 2 Preliminaries from Model Theory and Logic -- 3 Array-Based Artifact Systems: General Framework -- 4 Safety Verification of Artifact Systems -- 5 Decidability Results via Termination of the Verification Machinery -- 6. Preliminaries For (Uniform) Interpolation -- 7 Uniform Interpolation for Database Theories -- 8 Combination of Uniform Interpolants for DAPs Verification -- 9 MCMT: a Concrete Model Checker for DAPs -- 10 Business Process Management and Petri Nets: Preliminaries -- 11 DABs: a Theoretical Framework for Data-Aware BPMN -- 12 delta-BPMN: the operational and implemented counterpart of DABs -- 13 Catalog Object-Aware Nets -- 14 Conclusions -- References.

This book is a revised version of the PhD dissertation written by the author at the University of Bozen-Bolzano in Italy. It presents a new approach to safety verification of a particular class of infinite-state systems, called Data-Aware Processes (DAPs). To do so, the developed technical machinery requires to devise novel results for uniform interpolation and its combination in the context of automated reasoning. These results are then applied to the analysis of concrete business processes enriched with real data. In 2022, the PhD dissertation won the “BPM Dissertation Award”, granted to outstanding PhD theses in the field of Business Process Management. .

9783031427466

10.1007/978-3-031-42746-6 doi


Business--Data processing.
Artificial intelligence.
Business information services.
Business Informatics.
Artificial Intelligence.
IT in Business.

HF5548.125-.6

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