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Artifact Systems with Data Dependencies and Arithmetic*

机译:具有数据依赖性和算法的工件系统*

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We revisit 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-post conditions, 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. In previous work we identified the class of guarded artifact systems and properties, for which verification is decidable. However, the results suffer from 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 paper, we extend the artifact model and verifi cation 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 our previous work. While the worst-case complexity of verification is non-elementary, we identify various realistic restrictions yielding more palatable upper bounds.
机译:我们重新审视以数据为中心的业务流程的静态验证问题,该问题在IBM“业务工件”模型的变体中指定。工件是与业务相关的对象相对应的变量的记录,并由一组具有前后条件的服务来更新,这些条件实现了业务流程任务。验证问题在于静态检查工件系统的所有运行是否满足线性时间时序逻辑的一阶扩展表示的期望属性。在以前的工作中,我们确定了受保护工件系统和属性的类别,可以确定对其进行验证。但是,结果受到一个重要的局限性:即使存在非常简单的数据依赖项或算法,它们对现实的业务流程都至关重要,因此失败。在本文中,我们扩展了工件模型和验证结果以减轻这种限制。我们确定了具有数据依赖性和算法的业务工件,这在实践中是非常重要的,对于这些工件,可以确定验证。确定结果所需的技术机制与我们以前的工作根本不同。尽管最坏的情况下验证的复杂性是根本的,但我们确定了各种现实的限制,这些限制会产生更可口的上限。

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