科研之友
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摘要
Context: Business Processes provide a universal method of describing operational aspects of business. Business Rules, in turn, support declarative specification of business domain knowledge. Although there is a difference in abstraction levels between these both modeling techniques, rules can be complementary to processes. Rules can be efficiently used to specify process low-level logic, while processes can serve as a procedural specification of the workflow, including the inference control. Objective: One of the research problems in this area is supporting business analytics in the modeling of processes integrated with rules. Such a support can take advantage of new design method for such models. Method: We describe a model of procedural Business Process as well as the model and method of creating Attribute Relationship Diagrams. Based on these two representations, we provide a formalized model combining a process model with rules. Using these models, we introduce an algorithm that generates an executable process model along with decision table schemas for rules (rule templates for rule sets grouped in decision tables). Results: The paper provides an automated approach for generation of Business Process models from Attribute Relationship Diagrams. The approach was evaluated based on the selected benchmark cases, which were deployed and tested in the provided modeling and execution environment for such integrated models. Conclusion: The paper presents an efficient and formalized method for design of processes with rules that allows for generating BPMN models integrated with the rules from the Semantic Knowledge Engineering approach. Such a model can be treated as a structured rule base that provides explicit inference flow determined by the process control flow.
- 出版日期2017-11
