Conditional Foreign-Key Validation in Business Configuration
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Solution Overview
Problem
Managing consistency across complex business configuration processes in modern cloud business software systems is challenging, especially with large numbers of configuration tables and conditional foreign-key relations, which can lead to errors if not validated properly.
Innovation Solution
A business configuration framework with a configuration consistency validation processor that determines validation definitions and applies them before deploying configuration data to the target system, ensuring consistency by handling conditional foreign-key relations and delta validation to reduce unnecessary validation checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all configuration data is validated to ensure consistency, then system reliability is improved, but validation time and processing overhead increase
Solution Approach 1:
The validation process is segmented into multiple phases: pre-validation (determining validation definitions before deployment), during-validation (validating configuration data against definitions), and post-validation (handling validation results). This segmentation allows the system to validate only necessary configuration data at appropriate times, reducing overall validation time while maintaining consistency.
Solution Approach 2:
Validation definitions are determined in advance (pre-validation) before the actual configuration data validation occurs. The system pre-processes configuration data to identify conditional dependencies and creates validation definitions that specify what needs to be validated, when, and how. This preliminary action reduces the time required during actual validation by having preparation work completed beforehand.
2Reliability
If validation is performed on all configuration tables including those without changes, then configuration consistency is ensured, but processing efficiency decreases
Solution Approach 1:
The validation process applies different validation strategies to different configuration tables based on their specific characteristics. Configuration tables that have changed are validated thoroughly, while unchanged tables are either skipped or subjected to lighter validation. The system determines validation scope locally for each table based on change detection and dependency analysis, rather than applying uniform validation to all tables.
Solution Approach 2:
The system performs partial validation by validating only the necessary portion of configuration data. Instead of validating all configuration tables, the system identifies and validates only those tables that are relevant to the current changes and their dependencies. This partial action approach maintains consistency where needed while avoiding unnecessary validation of unchanged configuration data.
3Manufacturing precision
If complex conditional foreign-key relations are validated thoroughly, then data accuracy is improved, but validation complexity increases
Solution Approach 1:
Validation definitions serve as an intermediary layer between the complex conditional foreign-key relations and the validation process. Instead of directly implementing complex validation logic for each conditional dependency, the system uses validation definitions to describe the validation requirements. These definitions act as mediators that simplify the validation process by providing a standardized interface for handling complex relationships.
Solution Approach 2:
The system handles conditional foreign-key relations by changing validation parameters based on configuration values. Instead of using a single complex validation rule, the system adjusts validation parameters dynamically based on the specific configuration data being validated. This allows the same validation framework to handle various conditional scenarios by simply changing parameters rather than changing the underlying validation logic.
Data Source
AI summary
Configuration data is received characterizing configuration information of at least one application process executing on a target system. The configuration data includes a first table, a second table, and a third table. The first table includes a first conditional dependency on the second table and a second conditional dependency on the third table. The receiving is performed prior to transmission of the configuration data to the target system for application of the configuration data to the target system. At least one validation definition including a header and table elements specifying the first conditional dependency and the second conditional dependency is determined using the configuration data. Whether to validate the configuration data to ensure consistency within the target system is determined using the at least one validation definition. The determination of whether to validate the configuration data is provided. Related apparatus, systems, techniques and articles are also described.