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Optimal Test Strategy Generation Method Based on Nested Heuristic Functions for Complex Systems
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DOI：10.1109/TIM.2026.3677995.png)
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Abstract
En 中文
Design for testability (DFT) is an approach used to plan test strategies during the design phase, and ensure fault diagnosis capability during the use phase of a product. Due to the limited information available during the design phase, current mainstream approaches often rely on expert knowledge to construct multisignal flow graph (MSFG) models of the system. The test strategy is then formulated by solving the optimal strategy generation problem (OSGP). However, as the scale and complexity of systems continue to increase, the difficulty of solving the OSGP has grown significantly. Especially in large and complex systems, the test cost of strategies generated by existing algorithms can be quite high, severely limiting the maintainability of the system. To address these issues, this article proposes a nested method suitable for various heuristic functions. This method enhances the solving capability of OSGP by constructing a multilayer heuristic function structure. First, a nesting mechanism for heuristic functions is proposed. Then, it is demonstrated that, as the number of nested layers increases, the generated solution can converge to the global optimal solution. Finally, the required number of nested layers for different heuristic functions under a given maximum error constraint is derived, and algorithmic complexity is analyzed. The simulation and experimental results show that, for large-scale complex systems, the proposed method can reduce test costs by 11.5%–64.2% while ensuring fault isolation rate (FIR), significantly improving system testability.
Keywords:
Complex system
design for testability (DFT)
nested heuristic function
optimal strategy generation problem (OSGP)
test cost
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