Business processes involve data that can be modified and updated by various activities at any time. The data involved in a business process can be associated with flow elements or data stored in a persistence layer. These data must satisfy the business compliance rules associated to the process, where business compliance rules are policies or statements that govern the behaviour of a company. In order to improve and automate the validation and diagnosis of compliance rules based on the description of data semantics (called Business Data Constraints), we propose a framework where dataflow variables and stored data are analysed. The validation and diagnosis process is automated using Constraint Programming, since it permits the detection and identification of the possibly unsatisfiable business data constraints in an efficient way, even if the data involved in these constraints are not all instantiated. This implies that the potential errors can be determined in advance. Furthermore, a language to describe Business Data Constraints is proposed, for the improvement of the user-oriented aspects of the business process description. This language allows the business expert to write Business Data Constraints that will be automatically validated in run-time, without the support of the information technology expert.
The configuration of the Validation and diagnosis process is formed by four parts:
- Modeling the business process and define the dataflow variables (0:00-2:08)
- Locating the validation points (2:08-3:12)
- Creating the Business Data Constraints (3:12-5:15)
- Instantiating the Business Process Model (5:15-7.02)