Electronic device testability modeling evaluation method

Abstract

The invention discloses an electronic device testability modeling evaluation method, and relates to the technical field of device testing. The electronic device testability modeling evaluation method comprises the following steps of 1) determining the modeling object; 2) building a testability hierarchical mixture model; 3) adjusting, correcting and verifying the built testability hierarchical mixture model, and evaluating the accuracy of the built model; and 4) analyzing and evaluating the device testability. The electronic device testability modeling evaluation method has good observability, the association and dependency relation between faults and tests can be reflected, and the structural relation and the fault propagation relation between system modules can be reflected; multi-source testability information can be fused to carry out testability quantitative analysis and evaluation, at the same time, the electronic device testability modeling evaluation method has hierarchy, small fragment testability models such as subsystems or function modules are combined to form the testability model of the whole system, the modeling difficulty level is reduced, and the testability model can be extended and modified conveniently.

Description

technical field [0001] The invention relates to the technical field of equipment testing. Background technique [0002] During the demonstration and design stage of the equipment scheme, early test evaluation can be achieved by establishing a test model. At the same time, with the deepening of equipment development, the model should also be able to integrate test information such as expert experience information and historical test data generated in the process of equipment development, so as to improve the accuracy of test simulation evaluation results. [0003] At present, there are still three deficiencies in model-based test simulation evaluation: [0004] (1) Models based on determinism cannot handle the uncertainty of testing, such as information flow models, multi-signal flow graph models, etc.; [0005] (2) A model that can deal with test uncertainty, but cannot reflect the hierarchical structure of equipment, which is inconvenient for the evaluation of testability...

AI Technical Summary

Problems solved by technology

[0004] (1) Models based on certainty cannot deal with the uncertainty of testing, such as information flow models, multi-signal flow graph models, etc.;

[0005] (2) A model that can deal with test uncertainty, but cannot reflect the hierarchical structure of the equipment, is not convenient for the testability prediction and evaluation in the early stage of equipment design, such as the testability Bayesian network model;

[0006] (3) It is unrealistic to determine the conditional probability of nodes in the testable model through a large number of experiments. Most of the results are directly given based on assumptions or expert experience, and the processing is relatively rough, resulting in low accuracy of testable simulation evaluation results

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