Fault injection parameter processing method and device based on test process context

CN122019137APending Publication Date: 2026-05-12BEIJING AEROSPACE MEASUREMENT & CONTROL TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING AEROSPACE MEASUREMENT & CONTROL TECH
Filing Date
2025-12-29
Publication Date
2026-05-12

AI Technical Summary

Technical Problem

In existing technologies, the generation of fault injection parameters is disconnected from the global context of the test process and cannot be dynamically coordinated with the real-time system resource status. This results in low test automation, poor parameter adaptability, and insufficient robustness, especially inefficient in complex multi-step test scenarios.

Method used

By receiving test descriptions from the Automated Test Markup Language (ATML), extracting process context information, determining fault injection parameters using the Constraint Satisfaction Problem (CSP) model, and scheduling based on real-time resource status using a multi-objective optimizer, hardware resource instructions are generated to achieve dynamic adaptive fault injection.

Benefits of technology

It improves the accuracy and reliability of testing, ensures consistency between fault injection and test logic, enhances the robustness of complex test processes, optimizes resource utilization efficiency, reduces resource idleness and conflicts, and improves overall test throughput.

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Abstract

The invention provides a fault injection parameter processing method and device based on a test process context, and the method comprises the steps: obtaining process context information containing a multi-step logic relation through analyzing a test process described by an ATML (Automatic Test Markup Language); according to the process context information and the real-time resource state of the current test system, collaborative analysis and dynamic decision making are carried out, and adaptive fault injection parameters are intelligently generated; and finally executing fault injection according to the generated parameters. According to the method, the defects of fixed fault parameters and lack of process adaptability in a comprehensive test in the prior art are overcome, the conversion from static parameter table lookup to dynamic context sensing decision is realized, and the automation level, test precision and adaptability to complex test scenes of aviation tests and tests are remarkably improved.
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