Code Block Refactoring to Resolve Dependency Conflicts
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Solution Overview
Problem
The integration of modernized code with source code is challenging due to issues such as conflicting dependencies, outdated libraries, and inconsistent coding styles, leading to compatibility problems and significant latency in conventional products.
Innovation Solution
A computer-implemented method and system that refactors source code blocks by identifying dependent and exclusive blocks, generating refactoring options, and combining them to form an updated application, using AI-based models to ensure seamless co-existence and mutual consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If modernized code is integrated with source code, then code functionality is improved, but compatibility issues and conflicts arise due to differing dependencies and libraries
Solution Approach 1:
The codebase is divided into source code blocks that are evaluated and categorized as dependent or exclusive. This segmentation allows modernized code to be integrated in controlled increments, with each block independently refactored and tested, reducing compatibility conflicts between different dependencies and libraries
Solution Approach 2:
An AI-based code analysis system acts as an intermediary between source code and modernized code. This intermediary evaluates code blocks, identifies dependency conflicts, generates refactoring options, and ensures compatibility, mediating the integration process to prevent harmful conflicts
2Reliability
If code updates are performed to fix bugs and security vulnerabilities, then code reliability is improved, but the update process becomes complex and time-consuming
Solution Approach 1:
Before performing code updates, the system performs preliminary evaluation of code blocks to identify their dependency relationships. This preliminary action categorizes blocks as dependent or exclusive, preparing the structure needed for seamless integration and reducing the complexity of the actual update process
Solution Approach 2:
The AI-based system automatically evaluates code blocks, generates refactoring options, and guides the update process without requiring manual intervention for each step. This self-service capability reduces update complexity by automating the analysis and integration workflow
3Adaptability or versatility
If modernized functions are integrated with source code, then code adaptability is improved, but managing dependencies and ensuring consistency becomes demanding
Solution Approach 1:
The system provides feedback by evaluating code blocks and generating refactoring options that maintain consistency between source code and modernized code. This feedback mechanism guides dependency management by identifying conflicts and suggesting resolutions, making the process easier to operate
Solution Approach 2:
The system changes the state of code blocks from unevaluated to evaluated, and from dependent to exclusive through refactoring. These parameter changes track the integration progress and automatically manage dependencies, reducing the operational burden of ensuring consistency
Data Source
AI summary
A computer-implemented method, according to one approach, is for refactoring a number of source code blocks. The computer-implemented method includes evaluating the source code blocks and identifying dependent and exclusive ones of the source code blocks. The exclusive source code blocks are automatically refactored and options outlining how the dependent source code blocks can be refactored are generated. Moreover, the generated options are transmitted to a user. In response to receiving a selection of one or more of the options from the user, the dependent source code blocks are refactored as outlined in the selected one or more options. Furthermore, the refactored exclusive source code blocks and refactored dependent source code blocks are combined to form an updated application and corresponding updated service.


