Test Abstraction Data Model for Instrument-DUT Matching
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Solution Overview
Problem
Matching an appropriate instrument to a device-under-test (DUT) for effective testing is challenging due to the variety of DUTs and instruments available, requiring improved methods to ensure accurate and efficient testing procedures.
Innovation Solution
Constructing data structures based on instrument and test procedure specifications, including attributes, phenomena, and interactions, to determine matching conditions between instruments and DUTs, facilitating the selection of suitable instruments for specific testing procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual matching of instruments to DUTs is performed, then flexibility in instrument selection is maintained, but time consumption and complexity increase significantly
Solution Approach 1:
The system performs preliminary actions by constructing data structures from instrument data sheets and test procedure specifications before the actual matching process. These pre-constructed data structures contain all necessary attributes, phenomena, and interactions, enabling rapid automated comparison and matching without manual intervention during the actual testing workflow.
Solution Approach 2:
The patent introduces an intermediary automated matching system that acts as a mediator between instrument specifications and test procedure requirements. This intermediary system uses structured data comparison to automatically determine compatibility, replacing manual matching processes and significantly reducing time consumption while maintaining accuracy.
2Measurement precision
If comprehensive data structures are constructed for all instruments and test procedures, then matching accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the comprehensive matching problem into distinct components: instrument data structures containing attributes, phenomena, and interactions; test procedure data structures with corresponding specifications; and a systematic comparison process that evaluates each component separately. This segmentation enables accurate matching while managing complexity through modular organization.
Solution Approach 2:
The system transforms unstructured instrument data sheets and test procedure specifications into structured data formats with standardized parameters and attributes. This parameter transformation enables systematic comparison and automated matching, improving accuracy while the structured format actually reduces processing complexity compared to handling unstructured data.
3Productivity
If automated matching systems are implemented, then time consumption is reduced, but system complexity increases
Solution Approach 1:
The patent creates simplified data structure representations (copies) of complex instrument specifications and test procedures. These data structures capture essential matching criteria without requiring the full complexity of the original systems, enabling automated comparison and matching while keeping the automated system itself relatively simple to implement and maintain.
Data Source
AI summary
Methods and computing devices for matching an instrument to a device-under-test for performing a test procedure. A first data structure is constructed based on a data sheet of an instrument. The first data structure includes attributes, phenomena to be measured and testing interactions for measuring respective phenomena. A test case is constructed based on a test procedure to be performed on the DUT. The test case includes attributes, phenomena to be measured and testing interactions for measuring respective phenomena. The attributes, phenomena, and testing interactions of the first data structure and the test case are compared to determine a matching condition, and instructions are output based on the matching condition.