Source-Code Analysis for Domain-Driven Microservices Generation
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Solution Overview
Problem
Existing methods for modernizing applications face challenges in replicating enterprise value and extracting technical and business rules from legacy code, leading to incomplete and ambiguous results due to manual tracing and human error, which hampers the generation of optimized microservices-based architectures.
Innovation Solution
A system and method that automatically generates domain-driven microservices-based architecture from application source codes by parsing control flow structures to extract metadata, identify relevant data, and establish correlations between entities and actions, creating bounded contexts for efficient deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracing methods are used to extract technical and business rules from legacy code, then experts can identify critical business rules, but the process is time-consuming, laborious, and prone to human error and incompleteness
Solution Approach 1:
The patent replaces manual mechanical tracing with automated static code analysis tools that use algorithms to extract technical and business rules from legacy source code. The system automatically parses code structures, identifies data flows, and extracts business rules without human intervention, thereby eliminating human error while significantly reducing the time required for extraction.
Solution Approach 2:
The system enables the legacy code itself to 'self-reveal' its business rules through automated analysis. The code analysis engine processes the source code and automatically generates business rule documentation, allowing the system to extract rules from itself without requiring external expert intervention for each extraction task.
2Reliability
If manual extraction methods are used, then some business rules can be identified, but the process is prone to ambiguity and human error leading to incomplete matches between new and old capabilities
Solution Approach 1:
The patent replaces error-prone manual extraction with automated static code analysis that systematically processes entire codebases. The system uses algorithmic approaches to trace data flows, identify business rules, and validate completeness, thereby improving reliability while managing complexity through automation rather than manual procedures.
Solution Approach 2:
The system incorporates feedback mechanisms where the code analysis engine continuously validates extracted business rules against the source code, ensuring completeness and accuracy. The automated process provides feedback loops that verify rule extraction quality and identify any missed or ambiguous rules, improving overall reliability of the extraction process.
3Loss of information
If conventional manual techniques are used for extraction, then some technical logic can be captured, but the process risks damage from incomplete match between new capabilities and old capabilities
Solution Approach 1:
The patent replaces slow manual extraction with high-speed automated code analysis that can process millions of lines of code rapidly. The system maintains completeness of business rule capture by using comprehensive static analysis techniques while achieving rapid modernization speeds that manual processes cannot match, thereby preventing information loss without sacrificing productivity.
4Productivity
If automated tools are used for static code analysis, then extraction speed improves, but the tools offer little support for vital connections to business behaviours
Solution Approach 1:
The patent segments the code analysis process into multiple specialized components: one component handles rapid static code analysis for speed, while another component specifically analyzes business behavior patterns and connections. This segmentation allows the system to maintain high extraction speed while separately capturing vital business behavior context that automated tools typically miss.
Solution Approach 2:
The system combines multiple analysis approaches into a composite extraction methodology: automated static code analysis is combined with business behavior pattern recognition and data flow tracing. This composite approach integrates the speed of automated tools with the contextual understanding of business behaviors, achieving both high productivity and complete information capture.
Data Source
AI summary
The present invention provides for a system and a method for generation of domain driven microservices-based architecture from application source codes. A control flow structure is created based on extracted technical rules from an application source code and metadata is extracted by parsing the control flow structure in real-time. A first data associated with a plurality of source entities and corresponding attributes is identified and a second data associated with a plurality of target entities based on an operation type is identified. A third data associated with a plurality of technical data in the application source code is identified based on an action performed by a user via an application corresponding to application source code and data trace between the first data, the second data and the third data is generated. Correlations are established to generate microservices code-based architecture for deployment on a target platform.