Automated Legacy Application Transformation via AI Process Mapping
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Solution Overview
Problem
Current methods for transforming legacy applications to new technologies are inefficient, requiring extensive manual effort, significant resources, and resulting in inconsistent outcomes due to the lack of automated processes and the need for manual documentation and user training.
Innovation Solution
A computer-implemented system and method that automates process and application transformation using AI, which includes a tracking interface for data acquisition, a storage component for managing user interactions, an optimization processor for generating an application model, a code generation processor for creating application code, and a workflow automation processor for deploying the code and continuously improving the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual approaches are used for application transformation, then flexibility and adaptability are maintained, but productivity is low and time consumption is high
Solution Approach 1:
The system performs preliminary actions by automatically capturing user interactions and generating process maps before the actual transformation coding begins. The optimization processor analyzes captured data and generates recommended process improvements in advance, preparing all necessary transformation specifications before manual intervention is needed.
Solution Approach 2:
The transformation system serves itself by automatically generating code from process maps without requiring manual coding intervention. The code generation processor translates optimized process maps into executable code automatically, and the workflow automation processor deploys the code without manual intervention, enabling the system to transform applications autonomously.
2Manufacturing precision
If extensive manual documentation and analysis are performed, then accuracy and completeness of transformation are improved, but loss of time and resources increase
Solution Approach 1:
The system creates a digital copy of the actual user interaction process by capturing mouse movements, clicks, and navigation paths. This digital replica of the process is then analyzed by the optimization processor to generate accurate process maps without requiring manual documentation, preserving transformation accuracy while eliminating time-consuming manual recording.
Solution Approach 2:
The system replaces manual mechanical documentation processes with automated electronic capture mechanisms. The tracking interface automatically records user interactions through software instrumentation, substituting the manual act of documenting processes with automated data collection that occurs transparently during normal application usage.
3Loss of information
If manual process analysis is conducted, then understanding of current processes is achieved, but device complexity and resource requirements increase
Solution Approach 1:
The tracking interface serves multiple functions simultaneously: it captures user interactions, monitors application performance, collects process data, and generates optimization recommendations. This multi-functional approach achieves complete process understanding without requiring separate complex systems for each function, reducing overall device complexity.
Solution Approach 2:
The system changes the parameters of data collection from manual observation to automated electronic tracking. By transforming the nature of data capture from human-based to machine-based, the system achieves more complete process information with less resource consumption, as automated tracking can continuously monitor without the limitations of manual analysis capacity.
4Productivity
If automated code generation is implemented, then productivity and consistency are improved, but measurement precision and verification requirements increase
Solution Approach 1:
The workflow automation processor implements feedback mechanisms that automatically verify generated code against the optimized process maps and capture actual execution results. This feedback loop enables continuous verification and validation of generated code, ensuring measurement precision while maintaining high productivity through automated generation.
Data Source
AI summary
The invention relates to computer-implemented systems and methods for implementing an automated process and application transformation solution. An embodiment of the present invention is directed to accelerating the digital transformation of legacy applications, e.g., moving older applications to new targeted solutions. An embodiment of the present invention is directed to creating a sequential approach to automating these stages using a combination of technologies and Artificial Intelligence (AI) capabilities. These AI capabilities further augment existing resources and enhance experiences.