Pseudo Language Abstraction for BPEL Variable Mapping
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Solution Overview
Problem
Conventional Business Process Execution Language (BPEL) and XSLT mappings fail to accurately detect and prevent errors in data mapping between complex variables with different hierarchical structures and data types, leading to potential data loss and errors during process orchestrations.
Innovation Solution
A pseudo language abstraction of BPEL is introduced, incorporating enhanced mechanisms for early error detection and schema-aware operations, such as the assign, append, and remove verbs, which analyze and validate data types and cardinality during design time and implement operations at runtime, ensuring data is correctly mapped and updated without losing existing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional BPEL and XSLT mappings are used for data mapping between complex variables, then the implementation is straightforward, but errors related to mapping complex variables into each other are not detected
Solution Approach 1:
The patent introduces an intermediary validation mechanism that acts as a mediator between the source and target complex variables. This validator analyzes the mapping operation, checks for compatibility between source and target variables, and detects errors before they occur. The intermediary component adds error detection capability without requiring fundamental changes to the BPEL/XSLT mapping approach.
Solution Approach 2:
The patent implements preliminary validation of complex variable mappings before the actual mapping operation executes. By analyzing the source and target variable structures, data types, and hierarchical arrangements in advance, the system detects potential errors and prevents incorrect mappings from occurring, thereby improving reliability without adding runtime complexity.
2Manufacturing precision
If developers manually ensure compatibility between source and target complex variables, then mapping accuracy improves, but developer workload and time consumption increase
Solution Approach 1:
The patent enables the mapping system to perform self-validation by automatically analyzing the compatibility between source and target complex variables. The validator independently checks data types, hierarchical structures, and field arrangements without requiring manual developer intervention. This self-service capability maintains high mapping accuracy while significantly reducing developer time and effort.
Solution Approach 2:
The patent changes the operational parameters of the mapping process by introducing automated validation rules that dynamically assess source and target variable compatibility. Instead of requiring developers to manually verify each parameter, the system automatically evaluates data types, cardinality constraints, and hierarchical relationships, thereby maintaining precision while reducing time investment.
3Reliability
If conventional BPEL assignments are used without validation, then the operation is simple and fast, but data fields may be overwritten by incorrect fields without detection
Solution Approach 1:
The patent applies preliminary anti-action by implementing validation checks that prevent incorrect field overwrites before they occur. The validator analyzes the mapping operation in advance, identifies potential data integrity issues, and blocks incorrect mappings from executing. This approach ensures data integrity while maintaining operational simplicity by handling validation automatically without requiring complex user actions.
4Reliability
If stage files and web services are used to ensure data consistency, then mapping reliability improves, but the process becomes time-consuming and error-prone
Solution Approach 1:
The patent extracts the essential validation functionality from complex workarounds involving stage files and web services. By isolating the core compatibility checking logic into a dedicated validator component, the system achieves data consistency through a streamlined process that eliminates the overhead and error-proneness of external stage files and web service calls, thereby improving productivity while maintaining reliability.
Data Source
AI summary
A pseudo language is provided for manipulating the complex variables associated with the orchestration flow. Verbs are specified in the pseudo language. The verbs cause operations to be performed on the complex variables during processing of the orchestration flow. A first verb of the verbs is specified with a first operation of the operations The first operation, when processed, transfers data from a first set of source elements in a source complex variable to new target elements in a target complex variable based on a description of a target schema of the target complex variable. The target complex variable does not include the first subset of source elements and the target schema includes the description of the first subset of the source elements.