A business process model represents the expected behavior of a set of process instances (cases). The process instances may be executed in parallel and may affect each other through data or resources. In particular, changes in values of data shared by process instances may affect a set of process instances and require some operations in response. Such potential effects do not explicitly appear in the process model. This paper addresses possible impacts that may be affected through shared data across process instances and suggests how to analyze them at design time (when the actual process instances do not yet exist). The suggested method uses both a process model and a (relational) data model in order to identify potential inter-instance data impact sets. These sets may guide process users in tracking the impacts of data changes and supporting their handling at runtime. They can also assist process designers in exploring possible constraints over data. The applicability of the method was evaluated using three different realistic processes. Using a process expert, we further assessed the usefulness of the method, revealing some useful insights for coping with unexpected data-related changes suggested by our approach.

翻译：业务流程模型表示一组流程实例（案例）的预期行为。流程实例可能并行执行，并通过数据或资源相互影响。特别地，流程实例共享数据值的变化可能影响一组流程实例，并需要相应操作。这些潜在影响在流程模型中并未明确体现。本文探讨了跨流程实例共享数据可能带来的影响，并提出了在设计阶段（实际流程实例尚未存在时）分析这些影响的方法。该方法同时使用流程模型和（关系）数据模型来识别潜在的实例间数据影响集。这些集合可指导流程用户在运行时追踪数据变化的影响并支持其处理，同时帮助流程设计师探索数据上的可能约束。通过三个不同真实流程对方法的适用性进行了评估。我们进一步借助流程专家评估了方法的实用性，获得了一些应对数据相关意外变化的有用见解，这些见解正是由我们提出的方法所揭示的。