Cloud Code Automation Tool for Migration Rule Modeling
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Solution Overview
Problem
The manual and time-consuming process of migrating business systems to the cloud is inefficient, with existing tools being platform-specific and lacking in reusability and extensibility, making them unsuitable for comprehensive analysis and code rectification.
Innovation Solution
A reusable and extensible model for defining cloud rules based on enterprise architecture blueprints, utilizing the Cloud Code Automation Tool (CcAT) framework for analysis, code correction, and automatic estimation of changes, which includes Java and C code analysis frameworks, dynamic execution engines, and report generation plugins.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis and migration process is used, then flexibility and customization are possible, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs self-service by automatically analyzing source code, detecting violations, and generating migration recommendations without requiring manual intervention at each step. The framework autonomously executes rules against the codebase and produces detailed reports, enabling the migration process to serve itself rather than relying on manual analysis.
Solution Approach 2:
The patent replaces the mechanical manual analysis process with an automated computational system. Instead of manually reviewing code and documenting violations, the system uses software frameworks to automatically scan, analyze, and report code violations, substituting human manual labor with automated mechanical processes.
2Adaptability or versatility
If existing cloud migration tools are used, then some analysis capability is provided, but they are platform-specific and lack reusability and extensibility
Solution Approach 1:
The framework achieves universality by designing a platform-agnostic architecture that can analyze code from multiple source platforms and target multiple cloud destinations. The rule-based system and profile mechanism allow the same framework to be reused across different cloud platforms (AWS, Azure, GCP) without requiring platform-specific tooling, thereby providing both adaptability and reusability.
Solution Approach 2:
The system incorporates dynamics through its extensible rule and profile architecture. Rules can be dynamically added, modified, or removed based on specific migration requirements, and profiles can be customized for different target platforms. This dynamic configurability allows the framework to adapt to various platforms while maintaining a reusable core structure.
3Measurement precision
If comprehensive code analysis is performed, then migration accuracy improves, but the complexity of the tool increases
Solution Approach 1:
The framework segments the complex code analysis task into manageable components: violation detection rules, profile configurations, and report generation modules. Each rule is an independent, reusable unit that can be individually configured and executed. This segmentation allows comprehensive analysis capability while keeping individual components simple and maintainable.
Data Source
AI summary
A computerized system and method of migrating an application from a source platform to a target platform, such as a cloud platform. A set of rules are developed that represent aspect of the target platform and the source code of the application to be migrated is analyzed to determine whether it violates any of these rules. In some embodiments, the source code could be automatically modified to correct for violations of the rules.