Legacy Code Transformation for Automated Cloud Compliance
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Solution Overview
Problem
Existing systems face challenges in efficiently converting legacy code to cloud-compliant code without manual intervention and addressing security threats unique to cloud environments, undermining the advantages of cloud migration for organizations with large installed code bases.
Innovation Solution
A system and method that transforms legacy code into cloud-compliant code through a series of automated transformations, including parsing, tokenization, functional separation, security enhancements, and containerization, while ensuring functionality and security compliance, using cloud development standards and rigorous testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If legacy code is automatically ported to the cloud using existing systems, then migration speed is improved, but technical issues arise requiring significant manual intervention
Solution Approach 1:
The patent introduces a cloud-compliance translation layer that acts as an intermediary between legacy code and cloud environment. This translation layer includes a cloud-compliance library with wrapper classes that automatically handle cloud-specific concerns (security, networking, storage) without requiring manual code modification, thus maintaining high automation while ensuring cloud compliance.
Solution Approach 2:
The patent replaces manual mechanical intervention with automated computational processes. A static analysis tool automatically scans legacy code for cloud-compliance issues, and a code generation tool automatically produces corrected code, eliminating the need for manual review and modification while maintaining compliance.
2Loss of time
If existing automated porting systems are used, then conversion time is reduced, but cloud-specific security threats are not addressed
Solution Approach 1:
The patent performs preliminary security hardening during the automated code conversion process itself, rather than as a separate subsequent step. The translation layer pre-configures security measures (identity management, encryption, network security groups) and the static analysis tool pre-identifies security vulnerabilities, addressing security concerns before deployment while maintaining efficient conversion.
3Reliability
If manual rewriting of legacy code is performed, then cloud compliance and security are improved, but time and resource consumption increase significantly
Solution Approach 1:
The patent creates a copy of the legacy application logic that runs within cloud-managed containers or serverless functions. Instead of manually rewriting the entire application, the system copies the business logic while wrapping it with cloud-compliant infrastructure and security layers, preserving the original code's functionality while ensuring cloud compliance.
4Ease of operation
If legacy code is migrated without transformation, then migration simplicity is maintained, but the code is not suitable for execution in the cloud
Solution Approach 1:
The patent segments the migration process into distinct automated layers: (1) business logic layer that remains unchanged, (2) translation layer that handles cloud-specific adaptations, and (3) infrastructure layer that provides cloud services. This segmentation allows simple automated migration while ensuring cloud suitability through the intermediate translation and adaptation layers.
Data Source
AI summary
A system and method include reception of first code associated with an on-premise runtime environment and a first programming language, identification of tokens associated with the first programming language in the first code, removal of state dependencies from the first code based on the identified tokens and on transformation data mapping one or more of the identified tokens to a respective code transformation, to generate second code, execution of performance transformations on the second code to generate third code, execution of functional tests on the third code, in response to a determination that the functional tests were passed, separation of the third code into functional units to generate fourth code, application of a security function to one or more of the functional units to generate fifth code, and deployment of the fifth code to a cloud-based runtime environment.


