Architecture Disorder Evaluation for Computing Systems
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Solution Overview
Problem
Current methodologies for designing technical architectures for computer systems lack quantitative evaluation, leading to potential system failures and inefficiencies due to the absence of objective measures for assessing architecture quality, which can result in uncontrolled entropy and chaos.
Innovation Solution
A method and computer program product that objectively evaluate the quality of a technical architecture by determining disorder values for architectural decisions within function points, summing these values to generate a total disorder value, and comparing it against a pre-defined threshold, using machine learning to assess function placement, data sources, and integration types, thereby providing a quantitative and repeatable assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual architecture design methodologies are used, then design process is simple and accessible, but architecture quality cannot be objectively measured leading to uncontrolled entropy
Solution Approach 1:
The patent replaces manual, subjective architecture evaluation with an automated computational system that uses algorithms to calculate disorder values. This substitution transforms the evaluation process from a mechanical/manual procedure to an automated information processing system, enabling objective measurement of architecture quality through calculated metrics rather than human judgment.
Solution Approach 2:
The patent introduces disorder values as an intermediary metric that mediates between the complex architecture structure and the quality assessment. These disorder values serve as a quantitative bridge, translating architectural characteristics into measurable indicators that can be aggregated and compared against thresholds to determine overall architecture quality.
2Reliability
If quantitative evaluation is implemented, then architecture quality can be objectively measured, but the evaluation process becomes complex requiring disorder value calculations
Solution Approach 1:
The patent segments the architecture evaluation into discrete function points, each with its own disorder value calculation. This segmentation breaks down the complex task of evaluating entire architecture into manageable units, where each function point can be independently assessed and then aggregated to determine overall architecture quality.
Solution Approach 2:
The patent transforms qualitative architectural characteristics into quantitative parameters through disorder values. By changing the parameter representation from subjective descriptors to numerical metrics, the system enables objective comparison and measurement of architecture quality across different systems and designs.
3Measurement precision
If disorder values are calculated for each function point, then comprehensive architecture assessment is achieved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary identification and categorization of function points before the actual disorder value calculations. This preliminary action organizes the evaluation targets in advance, allowing the subsequent calculation process to proceed efficiently by processing pre-identified function points rather than discovering and analyzing them during the evaluation phase.
Data Source
AI summary
A method, computer program product, and a system to generate a total disorder value for architecture of a computing system include a processor(s) obtaining architecture detail for the computing system (the computing system includes function point(s)), and requirements defining aspirational performance benchmarks for the function point(s). The processor(s) identifies physical computing components within the computing systems comprising associated with each of the function points. For each function point, the processor(s) identifies architectural decisions and determines a disorder value for each decision. The processor(s) generates a total disorder value for the architecture detail by summing the disorder values for each function point. The processor(s) determines if the total disorder value exceeds a pre-defined threshold total disorder value for the computing system.