Application and Data Dependency Mapping Across Disparate Platforms
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Solution Overview
Problem
Complex software-driven environments require substantial time and resources for system changes due to intricate interdependencies, necessitating large personnel and extensive testing, which is inefficient and costly.
Innovation Solution
A system comprising dependency harvester applications that automatically identify, translate, and manage application and data relationships across disparate platforms, generating standardized dependency data for visualization and error prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated dependency identification systems are implemented, then productivity and time-to-implementation are improved, but device complexity and initial resource requirements increase
Solution Approach 1:
The patent introduces an intermediary system comprising dependency harvester applications, translation services, and visualization interfaces that mediate between complex proprietary ecosystems and users. This intermediary automatically identifies, translates, and visualizes dependencies across disparate platforms, reducing the complexity burden on end users while maintaining comprehensive dependency management capabilities.
Solution Approach 2:
The system implements self-service capabilities where dependency harvester applications automatically discover, extract, and translate dependency information from various ecosystems without requiring manual intervention. The system autonomously navigates proprietary formats, identifies relationships, and presents standardized information, enabling the system to serve itself in managing complex dependencies.
2Reliability
If extensive simulation and testing are conducted to identify affected system elements, then reliability is improved, but loss of time and productivity are worsened
Solution Approach 1:
The patent implements preliminary action by automatically identifying and mapping all dependencies before any system changes are made. The dependency harvester applications continuously monitor and update dependency relationships in advance, so when changes are needed, the system already has an accurate map of affected elements, eliminating the need for time-consuming trial-and-error testing.
Solution Approach 2:
The system incorporates feedback mechanisms where the visualization interface provides real-time information about dependency relationships and potential impacts of proposed changes. This feedback loop allows users to make informed decisions without extensive simulation, as the system continuously monitors and reports on the state of dependencies across the ecosystem.
Data Source
AI summary
Systems for application and data dependency identification, visualization, and management. In some embodiments, a plurality of dependency harvester applications/plugins may be utilized to automatically source dependency data that is then translated and/or converted into a standardized format that is utilized to generate and/or identify dependency relationships, e.g., across disparate computing platforms and/or environments. The results of these automatically-identified dependencies may then be utilized, for example, to provide an interface to project implementation personnel that can point out and/or quantify predicted errors. Such an automated dependency identification/harvesting system can dramatically reduce both personnel and time-to-implementation costs of projects implemented in a computing environment, particularly where the computing environment comprises a plurality of complex data and/or application interdependencies and/or relationships.