Monolithic Application Target Element Identification Through FA Scoring
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Solution Overview
Problem
Monolithic applications face challenges in isolating specific functionalities for updates or modifications without impacting the entire system, with traditional methods being time-consuming and error-prone, and automated tools often failing to accurately determine target/core elements.
Innovation Solution
A method and system that extracts process and data elements from a monolithic application, calculates a Functionality Association (FA) score based on predefined attributes, assigns categories based on FA scores and threshold ranges, and determines target elements for modification or reuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual methods are used to identify and extract target elements from monolithic applications, then developers can understand interdependencies, but the process is time-consuming and error-prone
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computational system that uses machine learning models and algorithms to identify and extract target elements from monolithic applications, eliminating the need for manual code review and analysis while improving both speed and accuracy
Solution Approach 2:
The patent introduces an intermediary automated tool that acts as a bridge between the monolithic application codebase and the development team, using FA score calculation and category assignment to mediate the complex process of element identification and extraction
2Productivity
If automated tools are used to identify functionalities within monolithic applications, then the process speed increases, but accuracy in determining target/core elements deteriorates
Solution Approach 1:
The patent changes the parameters used by automated tools from simple keyword matching to a multi-parameter FA score system that evaluates functionality associations, element types, and contextual relationships, thereby maintaining high speed while improving accuracy in target element identification
Solution Approach 2:
The patent implements feedback mechanisms where the automated tool continuously refines its identification process by calculating FA scores, comparing results against predefined thresholds, and adjusting category assignments to improve accuracy while maintaining automated speed
3Ease of operation
If monolithic applications maintain tight integration of all components, then deployment simplicity is preserved, but ease of modification and isolation of specific functionalities deteriorates
Solution Approach 1:
The patent applies segmentation by automatically identifying and extracting discrete target elements from the monolithic codebase, enabling developers to isolate specific functionalities for modification while preserving the overall integrated deployment structure
Solution Approach 2:
The patent extracts target elements and their interdependencies from the monolithic application using automated analysis, allowing specific functionalities to be removed or modified without affecting the entire system, thereby improving adaptability while maintaining deployment simplicity
Data Source
AI summary
This disclosure relates to method and system for determining target elements from a functionality of a monolithic application. The method includes extracting a set of process elements and a set of data elements from the functionality of the monolith application. The method further includes determining a Functionality Association (FA) score for each element of the set of process elements based on a first set of predefined attributes, and each element of the set of data elements based on a second set of predefined attributes. The method further includes assigning a category from a plurality of categories to the each element of the set of process elements and the each element of the set of data elements based on the FA score and pre-defined threshold ranges. Further, the method includes determining the target elements based on the assigned category.


