Software Architecture Visualization Using GenAI and Runtime Data
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Solution Overview
Problem
Large organizations face challenges in maintaining up-to-date software architecture diagrams due to siloed environments and external audits requiring current, real-time information that is often not readily available.
Innovation Solution
A generative artificial intelligence (GenAI) model is trained on software architecture documents to understand correlations between text and diagram components, generating dynamic and real-time diagrams from various input sources, including runtime data and user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If software architects work in siloed environments managing individual software systems, then each architect can focus on their specific system, but the architects become unaware of the broader software architecture ecosystem and cannot provide real-time, comprehensive architecture diagrams for external audits
Solution Approach 1:
The patent merges individual software system architectures into a unified software architecture ecosystem view. The system combines architecture diagrams from multiple siloed systems and integrates them with runtime data to create a comprehensive, real-time representation of the entire ecosystem, allowing architects to maintain individual focus while providing holistic visibility.
Solution Approach 2:
The system implements feedback loops that continuously collect runtime data from individual software systems and update the unified architecture diagram in real-time. This feedback mechanism ensures the architecture representation remains synchronized with actual system states, providing up-to-date information for external audits without requiring architects to leave their individual system contexts.
2Ease of manufacture
If static architecture diagrams are used for external audits, then documentation can be created, but the diagrams are not made by the architect or completed with enough current information to fully understand the software system as it currently is in real-time
Solution Approach 1:
The patent transforms static architecture diagrams into dynamic, living representations that automatically update in real-time. The system continuously ingests runtime data from software systems and regenerates architecture diagrams to reflect current system states, ensuring the documentation remains accurate and reliable without requiring manual updates by architects.
Solution Approach 2:
The system enables self-updating architecture documentation by automatically collecting runtime data from software systems and generating updated diagrams without human intervention. This self-service mechanism ensures architecture information remains current and accurate, eliminating the gap between diagram creation and actual system state.
3Loss of information
If comprehensive software architecture diagrams are manually created to show the entire ecosystem, then complete architecture information can be provided, but the diagrams become outdated quickly and require continuous manual updates
Solution Approach 1:
The patent implements continuous automatic updates of architecture diagrams by continuously collecting runtime data from software systems and regenerating diagrams in real-time. This continuous action eliminates the need for periodic manual updates, maintaining complete and current architecture information without consuming architect time.
Solution Approach 2:
The system replaces the mechanical process of manual diagram creation and updating with an automated computational process. Runtime data is automatically collected, processed, and used to generate updated architecture diagrams, substituting human manual labor with an automated system that maintains continuous, accurate architecture documentation.
4Productivity
If external audits are performed with outdated architecture diagrams, then audits can be completed, but the audits cannot verify current licensing rights and identify compliance gaps accurately
Solution Approach 1:
The system prepares current, accurate architecture diagrams in real-time before external audits occur. By continuously maintaining up-to-date architecture representations that reflect the actual system state, the system ensures that when audits are performed, the most current information is available for verifying licensing rights and identifying compliance gaps.
Data Source
AI summary
An example operation may include one or more of storing software architecture diagrams in a data store, receiving runtime data from a plurality of different software systems within a software architecture, the runtime data comprising descriptions of events that occur during runtime between the different software systems of the software architecture, generating a diagram of the software architecture based on execution of a multi-modal generative artificial intelligence (GenAI) model on the runtime data and the software architecture diagrams stored in the data store, and displaying the diagram of the software architecture via a user interface.