Design-time Data Context Validation for Business Processes
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Solution Overview
Problem
Business analysts often design processes in isolation from IT execution, lacking a common vocabulary, which leads to issues like missing data, ambiguous entities, and authorization constraints, resulting in incomplete workflows and increased complexity.
Innovation Solution
A system that validates data in the design time of process-oriented activities by evaluating the data needed for execution among process artifacts, providing users with a comprehensive view of the data context and suggesting corrections to ensure complete data availability, thereby preventing errors at execution time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If business analysts perform process design disconnected from IT execution, then process design flexibility is improved, but data completeness and execution reliability deteriorate
Solution Approach 1:
The system performs preliminary validation of data context during the design phase by checking if required entities are available and accessible before the process executes. This prevents execution failures by identifying missing data, unauthorized entities, or constraint violations early in the design process, thereby maintaining both design flexibility and execution reliability.
2Ease of operation
If existing application programs permit workflow design without validation, then ease of operation is improved, but errors during execution increase
Solution Approach 1:
The system provides immediate feedback during workflow design by validating data context and reporting issues such as missing entities, authorization problems, or constraint violations. This feedback mechanism allows users to correct errors during design rather than discovering them during execution, maintaining ease of operation while improving execution correctness.
3Adaptability or versatility
If data validation is performed during execution time, then design flexibility is maintained, but productivity deteriorates due to late error detection
Solution Approach 1:
The system performs data context validation during the design phase rather than at execution time. By checking entity availability, authorization, and constraints beforehand, it enables early error detection and correction, thereby improving productivity without restricting design flexibility.
4Reliability
If users are required to model data flow on top of control flow, then data consistency is improved, but device complexity increases
Solution Approach 1:
The system automatically performs data context validation and consistency checking without requiring users to manually model data flow. By autonomously verifying entity availability, data accessibility, and constraint compliance, it ensures data consistency while avoiding the complexity of manual data flow modeling.
Data Source
AI summary
Validating executable data for interactions among a plurality of process artifacts at design time. A data context is created to include the plurality of process artifacts. The data context carries interaction rules among the plurality of process artifacts. The executable data from a data source is associated with the plurality of process artifacts in the created data context. A subset of the interaction rules is selected corresponding to at least one of the plurality of process artifacts. The associated executable data is validated when the associated executable data is in accordance with the selected subset of the interaction rules.