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VERIFAS: A Practical Verifier for Artifact Systems
Data-driven workflows, of which IBM's Business Artifacts are a prime exp...
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Formal Verification of Probabilistic SystemC Models with Statistical Model Checking
Transaction-level modeling with SystemC has been very successful in desc...
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Verification of Agent-Based Artifact Systems
Artifact systems are a novel paradigm for specifying and implementing bu...
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Plankton: Scalable network configuration verification through model checking
Network configuration verification enables operators to ensure that the ...
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The High-Assurance ROS Framework
This tool paper presents the High-Assurance ROS (HAROS) framework. HAROS...
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Data-Driven Application Maintenance: Views from the Trenches
In this paper we present our experience during design, development, and ...
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Grand Challenge: Optimized Stage Processing for Anomaly Detection on Numerical Data Streams
The 2017 Grand Challenge focused on the problem of automatic detection o...
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SpinArt: A Spin-based Verifier for Artifact Systems
Data-driven workflows, of which IBM's Business Artifacts are a prime exponent, have been successfully deployed in practice, adopted in industrial standards, and have spawned a rich body of research in academia, focused primarily on static analysis. In previous work, we obtained theoretical results on the verification of a rich model incorporating core elements of IBM's successful Guard-Stage-Milestone (GSM) artifact model. The results showed decidability of verification of temporal properties of a large class of GSM workflows and established its complexity. Following up on these results, the present paper reports on the implementation of SpinArt, a practical verifier based on the classical model-checking tool Spin. The implementation includes nontrivial optimizations and achieves good performance on real-world business process examples. Our results shed light on the capabilities and limitations of off-the-shelf verifiers in the context of data-driven workflows.
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