Transaction Management System for Mainframe Integration
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Solution Overview
Problem
Legacy mainframe systems require proprietary, difficult-to-understand data formats for transaction processing, leading to errors and lack of real-time monitoring and transaction management capabilities, making it challenging for modern applications to integrate and manage transactions efficiently.
Innovation Solution
A transaction management system with a processor, database, API module, and transaction import module that validates and converts data from modern formats like JSON or XML into proprietary formats, allowing for real-time validation, batch imports, and providing monitoring and rollback capabilities for transactional mainframes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proprietary fixed-length string data formats are used for mainframe transaction processing, then mainframe compatibility is achieved, but data format complexity and difficulty of human understanding increase
Solution Approach 1:
The patent introduces an intermediary layer (the system described in the patent) that translates between modern data formats (JSON, XML) and proprietary mainframe formats. This intermediary handles the format conversion automatically, allowing applications to use simple modern formats while maintaining compatibility with mainframe systems that require proprietary formats.
2Productivity
If batch processing with daily imports is used, then mainframe processing capabilities are utilized, but real-time monitoring and error detection capabilities are lost
Solution Approach 1:
The patent implements feedback mechanisms that provide real-time status information about transaction processing. The system monitors processing status, detects errors immediately rather than waiting for batch completion, and provides feedback to applications about successful or failed transactions. This enables real-time error detection while still utilizing batch processing for actual mainframe imports.
Solution Approach 2:
The system performs preliminary validation and processing checks before submitting transactions to the mainframe batch process. By validating data formats, checking required fields, and pre-processing transactions in advance, the system catches errors early and prepares data for efficient batch processing, reducing both validation time and batch processing time.
3Stability of the object's composition
If rigidly-defined proprietary data formats are required, then mainframe system integrity is maintained, but adaptability to modern applications and development flexibility decrease
Solution Approach 1:
The patent creates a universal interface layer that can handle multiple modern data formats (JSON, XML, and other structured formats) while maintaining a single standardized interface to the mainframe system. This multi-functional approach allows the system to adapt to different application requirements and data formats without compromising mainframe integrity, as all formats are normalized through the intermediary layer.
4Reliability
If custom programming is required to generate compliant data, then mainframe data format requirements are met, but development time and costs increase
Solution Approach 1:
The system implements self-service functionality where the intermediary automatically handles data format conversion and compliance validation. Applications don't need custom programming to generate compliant data because the system automatically transforms modern formats into mainframe-compliant formats, performs validation, and manages the entire conversion process without manual intervention or custom code.
Data Source
AI summary
In one aspect, the present disclosure relates to a system for improved transactional mainframes, the system comprising a processor, a database, an application programming interface (API) module, and a transaction import module. The API module can be configured to: receive transaction data comprising a transaction type, a user identifier, one or more transaction card identifiers, and one or more fields associated with the transaction card identifiers; validate the transaction data using one or more of the stored validation rules associated with the one or more transaction card identifiers; generate one or more transaction cards; and store the transaction data and transaction cards to the database. The transaction import module can be configured to submit the transaction cards to the mainframe, view the status of submitted records, and enable retrying of transaction cards that failed to process.


