JSON Data Verification via XML Conversion and SQL Comparison
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Solution Overview
Problem
Manual verification of JSON data from back-end data warehouses is time-consuming and incomplete, as it is impractical to cover all problem and error scenarios effectively.
Innovation Solution
An automated validation process is implemented by making a JSON call via an XML HTTP object against a data warehouse, converting JSON response data to XML, and comparing it with expected XML result data generated from SQL queries to verify data accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual verification of JSON data is performed, then data accuracy can be checked, but the process is time-consuming and incomplete
Solution Approach 1:
The system performs self-verification by automatically comparing JSON response data against expected data generated from SQL queries. The verification process is autonomous and does not require manual intervention, allowing the system to check its own output for accuracy and completeness.
Solution Approach 2:
The patent replaces manual mechanical verification processes with an automated computational system. Instead of human operators manually checking JSON data, the system uses programmatic comparison between actual JSON responses and expected XML data generated from database queries to perform verification.
2Reliability
If manual verification is used, then some data checking can be performed, but it is impractical to cover all problem and error scenarios
Solution Approach 1:
The verification system is designed to be universal and can handle multiple types of data scenarios, error conditions, and validation requirements through a single automated framework. The system can verify various data formats, handle different error scenarios, and provide comprehensive coverage without requiring separate verification processes for each case.
Solution Approach 2:
The system incorporates feedback mechanisms where the actual JSON response data is compared against expected data, and the results of this comparison are fed back to identify discrepancies, errors, and data quality issues. This feedback loop enables comprehensive detection of problems across all scenarios.
3Productivity
If automated verification is implemented, then verification efficiency improves, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary verification layer that sits between the JSON data generation and consumption components. This intermediary system handles the comparison and validation logic, separating the verification complexity from the core business logic and allowing for manageable system architecture.
Solution Approach 2:
The system changes the verification approach from manual to automated by transforming the verification parameters and processes. The system generates expected data parameters from SQL queries and compares them against actual JSON response parameters, enabling automated verification through parameter transformation and comparison.
Data Source
AI summary
Aspects provide for automatic verification of JavaScript Object Notation (JSON) data by making a JSON call via an Extensible Markup Language (XML) Hypertext Transfer Protocol (HTTP) HTTP object against a data warehouse data item stored in a back end server. JSON response data returned from the back end server in response to the JSON call is converted into actual XML result data that includes a first plurality of XML statements. A Structured Query Language (SQL) query is executed against the data warehouse data item, and expected XML result data generated in response thereto that include a different (second) plurality of XML statements. The JSON response data returned from the back end server is thereby verified in response to matching the actual XML result data to the expected XML result data.