Workflow Convergence Schema Auto-Population
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Solution Overview
Problem
In complex workflows with multiple conditionals, users face the time-consuming and error-prone task of manually mapping data responses across numerous paths, making it impractical to manage data mappings effectively.
Innovation Solution
The system identifies convergence points in a workflow, receives schema parameters, and stores data mapping input values structured according to these schemas, allowing for auto-population of data mappings at other outputs, thereby reducing the number of manual mappings required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data mapping is performed for each path in complex workflows with multiple conditionals, then complete data coverage is achieved, but time consumption and error rate increase significantly
Solution Approach 1:
The patent applies preliminary action by defining schemas at convergence points before data flows diverge through conditional paths. This allows the system to pre-establish data structure expectations at branching points, enabling automatic population of mapping parameters along all subsequent paths without manual intervention for each individual path.
Solution Approach 2:
The patent implements universality by creating a single schema definition at a convergence point that serves multiple divergent paths simultaneously. This universal schema definition automatically populates mapping parameters for all paths branching from that convergence point, eliminating the need for separate manual mapping configurations for each path while maintaining data accuracy across all routes.
2Reliability
If manual data mapping is performed for each path in complex workflows, then complete data coverage is achieved, but operational complexity increases
Solution Approach 1:
By performing the data mapping configuration action at convergence points before paths diverge, the system eliminates the need for operators to manually configure each individual path. The preliminary schema definition automatically propagates through all subsequent paths, maintaining completeness while dramatically improving ease of operation.
Solution Approach 2:
The patent uses copying by automatically replicating the schema definition and mapping parameters from a single convergence point definition across multiple divergent paths. This copying mechanism ensures complete data coverage is maintained while reducing operational effort from defining each path individually to defining only the convergence point.
3Productivity
If schemas are defined at convergence points with automatic population, then time and effort are reduced, but system complexity increases
Solution Approach 1:
The patent introduces an intermediary component that automatically handles the propagation and population of mapping parameters from convergence point schemas to individual path configurations. This intermediary mechanism manages the underlying system complexity while presenting a simplified interface to users, enabling fast workflow setup without requiring operators to understand or manage the complex population logic.
Solution Approach 2:
The system implements self-service by automatically populating mapping parameters along all paths branching from a convergence point without requiring manual intervention. The system serves itself by detecting the schema definition at the convergence point and autonomously propagating the mapping configuration through all subsequent paths, increasing productivity while encapsulating complexity within the automated population mechanism.
Data Source
AI summary
A computer-implemented method comprising: receiving, by a computing device, user input defining a workflow; receiving, by the computing device, information defining schemas at convergence points in the workflow; determining, by the computing device, a set of mapping parameters at outputs of nodes of the workflow based on the schemas; receiving, by the computing device, input values to the mapping parameters; storing, by the computing device, the input values to the mapping parameters in a structure corresponding to the schemas; and executing, by the computing device, the workflow based on the input values to the mapping parameters, wherein the executing includes invoking one or more applications residing on one or more application servers through application programming interface (API) calls.