Abstract.A promising approach to managing business operations is based on business entities with lifecycles (BEL's) (a.k.a. business artifacts), i.e., key conceptual entities that are central to guiding the operations of a business, and whose content changes as they move through those operations. A BEL type includes both an information model that captures, in either materialized or virtual form, all of the business-relevant data about entities of that type, and a lifecycle model, that specifies the possible ways an entity of that type might progress through the business by responding to events and invoking services, including human activities. Most previous work on BEL's has focused on the use of lifecycle models based on variants of finite state machines. This paper introduces the Guard-StageMilestone (GSM) meta-model for lifecycles, which is an evolution of the previous work on BEL's. GSM lifecycles are substantially more declarative than the finite state machine variants, and support hierarchy and parallelism within a single entity instance. The GSM operational semantics are based on a form of EventCondition-Action (ECA) rules, and provide a basis for formal verification and reasoning. This paper provides an informal, preliminary introduction to the GSM approach, and briefly overviews selected research directions.
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.
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