Automated POA&M Generation Engine for Code Review Data Extraction
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Solution Overview
Problem
Current systems lack automation for rapid user customization and error reduction in generating Plan of Action and Milestones (POA&M) documents from code review reports, leading to inefficiencies and increased risk in security, financial, and national security contexts.
Innovation Solution
The Plan of Action and Milestones Automated Generation Engine (PAGE) system uses scanning technologies, user interfaces, and an expert system to selectively scan networked systems, extract relevant data, and generate customizable POA&M outputs from code review reports, reducing errors and accelerating the analysis process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual cut and paste methods are used to create POA&M from code review reports, then system complexity remains low, but productivity is severely limited to 5,000 issues per week with high error risk
Solution Approach 1:
The system enables self-service automation where the POA&M generation process automatically extracts data from code review reports, populates templates, and generates outputs without requiring manual intervention for each issue. The automation engine processes reports independently, transforming unstructured data into formatted POA&M documents while maintaining accuracy and consistency across all generated content.
Solution Approach 2:
The patent replaces the mechanical manual process of cutting and pasting data with an automated information extraction system. The automation engine uses parsing algorithms and data transformation rules to substitute human manual operations, eliminating the need for repetitive manual data entry while significantly increasing throughput from 5,000 issues per week to potentially unlimited processing capacity.
2Reliability
If manual POA&M creation processes are used, then ease of operation is maintained, but reliability deteriorates due to significant human error risk in security and national security contexts
Solution Approach 1:
The system incorporates feedback mechanisms where the automation engine validates extracted data against predefined schemas and rules, checking for completeness and consistency. The system provides feedback loops that verify data extraction accuracy, template population correctness, and output generation validity, ensuring high reliability while maintaining ease of operation through automated validation rather than manual checking.
Solution Approach 2:
The patent introduces an intermediary automation layer between the code review reports and the final POA&M output. This intermediary system acts as a mediator that systematically transforms raw data into structured information, eliminating direct human involvement in the error-prone manual processes while preserving operational simplicity through a user-friendly interface that initiates and monitors the automated process.
3Productivity
If rapid automation is implemented for POA&M generation, then productivity increases significantly, but device complexity increases requiring sophisticated scanning and extraction systems
Solution Approach 1:
The patent applies segmentation by dividing the POA&M generation process into distinct modular components: a scanning module that identifies relevant data in code review reports, an extraction module that retrieves specific information, a transformation module that formats data according to templates, and an output generation module that produces final documents. This segmentation allows each component to be optimized independently while working together to achieve high throughput without overwhelming system complexity.
Solution Approach 2:
The automation engine is designed as a universal system capable of processing multiple types of code review reports from different sources and formats. The system uses standardized extraction rules and adaptable templates that can handle various report structures, enabling a single multi-functional platform to serve diverse needs while maintaining high productivity without proportionally increasing complexity.
4Measurement precision
If comprehensive data extraction is performed from code review reports, then measurement precision improves for security analysis, but loss of time increases due to the Herculean analysis task beyond human cognitive capacity
Solution Approach 1:
The system performs preliminary actions by pre-configuring extraction rules, data transformation logic, and template structures before the actual POA&M generation process. The automation engine is pre-programmed with knowledge of relevant data patterns, security criteria, and formatting requirements, enabling it to rapidly extract and process information without requiring time-consuming manual analysis while maintaining high measurement precision through predefined accuracy standards.
Solution Approach 2:
The patent implements continuous automated processing that operates without interruption throughout the POA&M generation workflow. The system maintains continuous useful action by processing multiple reports simultaneously, continuously extracting data, transforming information, and generating outputs in an unbroken workflow. This eliminates the time loss associated with human cognitive limitations and breaks, maintaining both high precision and rapid throughput through sustained automated operation.
Data Source
AI summary
Plan of action and milestones (POA&M) automated generation engine (PAGE) systems are provided along with related methods. A number of distributed tamper protected configuration scanning systems configured to scan computer files in selected target systems across a network and generate target system configuration scan results files. The PAGE system also includes a number of POA&M configuration selection user interfaces and visualization systems enabling users to select, inform, and customize POA&M outputs based on POA&M configuration files that include POA&M library files that are associated with different types of plans or actions (e.g., cyber security configuration for networked computers). An expert system is also provided for receiving a plurality of configuration file inputs (e.g., configuration scan results file and various baseline files, e.g., security configuration files, etc), comparing the scan results file and baseline files, then generating customized POA&M outputs based on the user interface(s) and/or visualization system(s) inputs or selections.