Automated Software Analysis for Pega Remediation
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Solution Overview
Problem
The scope of effort required to remediate Pega applications to utilize new technologies, such as cloud hosting and generative AI, is unclear, discouraging remediation efforts due to the lack of effective methods for identifying and estimating issues and remediation costs.
Innovation Solution
A method and system that analyze source code to generate metadata, identify issues, categorize them, and produce reports assessing the technical state of the software application, including remediation effort metrics like duration, cost, and productivity improvement, using a processor and user interface, with features like code complexity, security vulnerabilities, and test coverage analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated analysis tools are implemented to identify and estimate remediation issues, then measurement precision of remediation scope is improved, but device complexity of the analysis system increases
Solution Approach 1:
The patent introduces an automated analysis tool as an intermediary between the legacy codebase and the remediation planning process. This tool processes source code, generates metadata, identifies issues, and produces estimates, serving as a mediator that transforms complex code analysis into structured, actionable information without requiring direct human intervention in the analysis process.
Solution Approach 2:
The patent replaces manual code analysis and remediation estimation (mechanical human effort) with an automated computer-based system. The processor executes algorithms to analyze source code, generate metadata, and produce estimates, substituting human cognitive and manual labor with automated computational processes.
2Reliability
If comprehensive issue identification and categorization is performed, then reliability of remediation assessment is improved, but loss of time for analysis increases
Solution Approach 1:
The patent performs preliminary automated analysis of the source code to generate metadata and identify issues before formal remediation planning begins. This preliminary action includes categorizing issues and producing initial estimates, which are prepared in advance to guide subsequent remediation activities and reduce the time needed for detailed assessment.
Solution Approach 2:
The system provides feedback through structured reports that present categorized issues and remediation estimates to stakeholders. This feedback mechanism allows for informed decision-making about remediation priorities and resource allocation, enabling iterative refinement of the analysis focus based on business needs while maintaining comprehensive coverage.
Data Source
AI summary
Systems and methods to forensically inspect an existing set of rules built as a Pega application and output detailed metadata on the application's quality, technical debt, cloud readiness and upgradability. That metadata can be used to provide a detailed report on how to remediate and improve the application. In addition, a technical burndown analysis can be completed to show duration, cost savings and productivity details that can be achieved.