Automated Mainframe Refactoring via Dependency Modeling
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Solution Overview
Problem
Existing mainframe batch systems face complexity and risk in refactoring to a cloud native environment due to lack of a holistic understanding of their components and dependencies, leading to manual and competency-dependent translation processes.
Innovation Solution
An intelligent automation model that comprehends the mainframe ecosystem, creating a proprietary language independent model (PLIM) to represent elements and dependencies, using externalized command-based templates (ECBT) for seamless conversion to cloud native architecture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual refactoring of mainframe batch systems is performed, then expertise and competency are required to handle complexity, but the process is time-intensive and prone to failures
Solution Approach 1:
The patent introduces an intermediary refactoring system that acts as a mediator between mainframe batch systems and cloud native environments. This system automatically analyzes mainframe components, transforms them into cloud-native equivalents, and generates migration artifacts, eliminating the need for manual expert intervention while ensuring reliable transformation.
Solution Approach 2:
The patent replaces the mechanical manual process of expert analysts manually refactoring code with an automated computational system. The system uses algorithms to parse, analyze, and transform code automatically, substituting human mechanical effort with automated mechanical processes that are faster and more reliable.
2Productivity
If automated refactoring tools are used, then productivity increases, but understanding of complex mainframe ecosystem dependencies is lost
Solution Approach 1:
The patent performs preliminary actions by automatically discovering and mapping dependencies between mainframe components before the refactoring process begins. The system analyzes JCL, PROCs, control cards, and data sets to build a comprehensive dependency model, ensuring that all ecosystem relationships are captured prior to transformation.
Solution Approach 2:
The patent implements feedback mechanisms where the refactoring system continuously monitors and validates the transformed components against the original ecosystem dependencies. This ensures that the automated process maintains accurate understanding of component relationships and makes adjustments as needed to preserve ecosystem integrity.
3Manufacturing precision
If comprehensive analysis of all mainframe components is performed, then accuracy of transformation improves, but device complexity increases
Solution Approach 1:
The patent segments the complex mainframe ecosystem into distinct analyzable components including JCL, PROCs, control cards, data sets, and utilities. Each component type is processed independently through specialized transformation rules, making the overall complex system manageable while maintaining high transformation accuracy.
Solution Approach 2:
The patent creates a universal refactoring framework that handles multiple mainframe component types through a common architecture. The system uses unified dependency modeling and standardized transformation processes that work across different component types, reducing system complexity while maintaining comprehensive analysis capability.
Data Source
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AI summary
A Mainframe batch system have various type of source components and each component has its own purpose and functionality within the environment. Existing refactoring are still dependent on manual skills and competency. A method and system for automated refactoring of mainframe based batch systems to cloud native environment is provided. The present disclosure proposes an intelligent automation model that comprehends every aspect of the existing Mainframe batch system, all its inherent source elements along with its dependencies. With this holistic understanding of all the elements of the Mainframe batch system, the system converts the information within them into a proprietary conceptual model. This model has all the information about the source elements is converted into the target architecture which is cloud native. The combination of the model with the externalizable command based templates (EBCT) aligns the conversion to any target technology feasible.