Deep Systems Analysis
Why Deep Systems Analysis?
Deep Systems Analysis
This page describes the Deep Systems Analysis (DSA) methodology that forms the theoretical core of BERT.
What is Deep Systems Analysis?
Deep Systems Analysis is a rigorous methodology for understanding complex systems:
Origins in systems science and complexity theory
Focus on hierarchical decomposition with maintained relationships
Emphasis on flows and transformations across system boundaries
Preservation of structure-behavior relationships
Detailed DSA foundations coming soon...
Core Principles of DSA
The foundational principles that guide Deep Systems Analysis:
Systems are bounded entities with defined inputs and outputs
Every system can be decomposed into subsystems
Flows must be conserved across system boundaries
Interfaces mediate all interactions between systems
Structure determines behavior at all system levels
Detailed principles explanation coming soon...
The DSA Process
The step-by-step approach to applying Deep Systems Analysis:
Define the system of interest and its boundary
Identify external entities and their interactions
Establish system interfaces and flow patterns
Decompose into subsystems while preserving flows
Validate model consistency across levels
Iteratively refine the model
Detailed process guide coming soon...
DSA Validation
Ensuring your system analysis maintains rigor and consistency:
Boundary consistency checks
Flow conservation validation
Interface alignment across levels
Decomposition completeness criteria
Semantic validation techniques
Detailed validation methods coming soon...
Extending DSA
How DSA integrates with other systems analysis approaches:
Complementary frameworks (DSRP, SSM, VSM)
Extensions for specific domains
Computational applications of DSA
DSA for complex adaptive systems
Detailed extensions coming soon...
SOI Identification
Environmental Analysis
Recursive Decomposition
Fundamentally subjective
Related Sections:
Core System Elements
System Language Foundation
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