Composite Navigation for Automatic Configuration Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The reuse of complex configuration values in COTS software is hindered by the difficulty for domain experts and programmers to understand the behavior and relationships between logic fragments, leading to increased costs, risks, and inefficiencies in configuration management.
Innovation Solution
A composite navigational method and system that extracts previous configuration values, generates abstract syntax trees, and performs pre-specified operations to determine a navigation pattern, allowing for the automatic configuration management of application software based on user preferences and previous configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complex configuration values (logic fragments) are used to provide flexibility for different customer requirements, then adaptability is improved, but device complexity increases making it difficult for domain experts to understand and configure the system
Solution Approach 1:
The patent introduces an intermediary system (configuration management system with AI/ML components) that mediates between domain experts and complex configuration logic. The system automatically analyzes customer requirements, navigates through configuration options, and determines optimal configuration values without requiring domain experts to directly understand or write complex logic fragments, thus maintaining adaptability while reducing perceived complexity.
Solution Approach 2:
The configuration management system performs self-service by automatically analyzing requirements, navigating configuration spaces, and determining optimal configuration values using AI/ML algorithms. This eliminates the need for domain experts to manually configure complex logic fragments, allowing the system to serve itself in configuring while maintaining high adaptability to different customer needs.
2Productivity
If configuration settings are reused from previous configurations to reduce development effort and cost, then productivity is improved, but reliability decreases due to difficulty in understanding behavior and relationships between logic fragments
Solution Approach 1:
The patent implements feedback mechanisms where the AI/ML-based configuration management system continuously learns from configuration outcomes and performance data. By analyzing whether reused configurations meet customer requirements and system performance targets, the system provides feedback to improve future configuration selections, thereby maintaining reliability while enabling reuse of configuration settings across different deployments.
Solution Approach 2:
The system performs preliminary analysis and validation of configuration values using AI/ML algorithms before deployment. By pre-evaluating the suitability and expected behavior of configuration settings from previous configurations, the system ensures reliability is maintained while enabling rapid reuse of proven configuration patterns, reducing both development effort and risk.
3Manufacturing precision
If expert programmers are involved to translate domain requirements into logic fragments, then manufacturing precision is improved, but loss of time increases due to involvement of specialized personnel
Solution Approach 1:
The patent replaces the mechanical process of manual translation by expert programmers with an automated AI/ML-based configuration management system. The system uses natural language processing and machine learning to automatically translate domain requirements into appropriate configuration values, eliminating the need for expert programmer involvement while maintaining translation accuracy and significantly reducing the time required.
Solution Approach 2:
The configuration management system performs self-service in translating requirements into configuration values using AI/ML algorithms. By automatically analyzing domain requirements and determining optimal configuration settings without human intervention, the system maintains manufacturing precision while eliminating time loss associated with expert programmer involvement.
4Reliability
If configuration values are written from scratch rather than reused to ensure correctness, then reliability is improved, but productivity decreases due to increased development effort
Solution Approach 1:
The AI/ML-based configuration management system performs preliminary analysis and validation of configuration values from previous configurations before recommending them for reuse. By pre-evaluating the correctness and suitability of existing configuration settings through automated algorithms, the system ensures reliability is maintained while enabling productivity gains from reuse, eliminating the need to write configurations from scratch.
Solution Approach 2:
The system implements feedback loops that continuously validate and learn from configuration outcomes. By monitoring whether reused configurations produce correct and desired system behavior, the system builds confidence in reuse decisions over time, maintaining reliability while enabling increased productivity through systematic configuration reuse rather than repeated from-scratch development.
Data Source
AI summary
The disclosed embodiments illustrate a composite navigational method and system for the automatic configuration management of application software by a computing server. The method includes extracting a plurality of previous configuration values from a storage device. The method further includes generating a plurality of abstract syntax trees (ASTs) based on parsing of the plurality of previous configuration values. The method further includes performing one or more pre-specified operations on the generated plurality of ASTs. The method further includes determining a configuration value of a current configuration parameter based on a navigation pattern, such as hierarchical navigation or variable-based filtering navigation. Further, the navigation pattern is determined using the performed one or more pre-specified operations, based on at least user preferences and the extracted plurality of previous configuration values. The method further comprising controlling the configuration of the application software based on the determined configuration value of the current configuration parameter.