Physical-Defect Modeling and Optimization for Fault-Insertion Test

Hardware fault insertion is a promising method for system reliability assessment and fault isolation. It provides feedback on the fault tolerance of a large system, creates artificial faulty scenarios that can be used as reference points for fault diagnosis, and leads to a quality diagnostic program. Optimization of fault insertion location is critical for accelerating the assessment of system reliability and constructing a complete knowledge base for fault diagnosis. In this work, we construct a pin-level fault model that is able to effectively mimic the errors (effects) caused by physical defects within the component. A simulation framework and optimization techniques are proposed to select a minimum subset of output pins that can represent as many physical defects as possible. The optimization results provide guidelines on the fault insertion locations and the appropriate fault types for insertion. In addition, three intrinsic characteristics of output pins, including testability number, fan-in size, and transition counts, are analyzed. The effectiveness of the proposed model is evaluated in terms of impact on system response and error-detection latency. Experimental results are presented for OpenCore benchmarks.