Affiliation:
1. Microsoft
2. University of California, San Diego, CA
Abstract
We study the static verification problem for data-centric business processes, specified in a variant of IBM's “business artifact” model. Artifacts are records of variables that correspond to business-relevant objects and are updated by a set of services equipped with pre- and postconditions, that implement business process tasks. The verification problem consists in statically checking whether all runs of an artifact system satisfy desirable properties expressed in a first-order extension of linear-time temporal logic. Previous work identified the class of
guarded
artifact systems and properties, for which verification is decidable. However, the results suffer an important limitation: they fail in the presence of even very simple data dependencies or arithmetic, both crucial to real-life business processes. In this article, we extend the artifact model and verification results to alleviate this limitation. We identify a practically significant class of business artifacts with data dependencies and arithmetic, for which verification is decidable. The technical machinery needed to establish the results is fundamentally different from previous work. While the worst-case complexity of verification is nonelementary, we identify various realistic restrictions yielding more palatable upper bounds.
Funder
Division of Information and Intelligent Systems
Publisher
Association for Computing Machinery (ACM)
Cited by
46 articles.
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